Publications by Christian Igel

Matthias Freiberger, Peter Kun, Christian Igel, Anders Sundnes Løvlie, and Sebastian Risi. Fooling Contrastive Language-Image Pre-Trained Models with CLIPMasterPrints. Transactions on Machine Learning Research, accepted

Pedram Bakhtiarifard, Christian Igel, and Raghavendra Selvan. EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), accepted

Nico Lang, Vésteinn Snæbjarnarson, Elijah Cole, Oisin Mac Aodha, Christian Igel, and Serge Belongie. From Coarse to Fine-Grained Open-Set Recognition. Computer Vision and Pattern Recognition (CVPR), accepted

Martin Brandt, Maurice Mugabowindekwe, Athanase Mukuralinda, Philippe Ciais, Florian Reiner, Ankit Kariryaa, Christian Igel, Jerome Chave, Ole Mertz, Pierre Hiernaux, Xiaoye Tong, Gaspard Rwanyiziri, Dimitri Gominski, Sizhuo Li, Siyu Liu, Ivan Gasangwa, Yves Hategekimana, Alain Ndoli, Jean Nduwamungu, Sassan Saatchi, and Rasmus Fensholt. Trees on smallholder farms and forest restoration are critical for Rwanda to achieve net zero emissions. Communications Earth & Environment 5:113, 2024

Bjørn Leth Møller, Bobby Zhao Sheng Lo, Johan Burisch, Flemming Bendtsen, Ida Vind, Bulat Ibragimov, and Christian Igel. Building an AI Support Tool for Real-time Ulcerative Colitis Diagnosis. Künstliche Intelligenz, 2024

Stefan Oehmcke, Lei Li, Jaime Revenga, Thomas Nord-Larsen, Katerina Trepekli, Fabian Gieseke, and Christian Igel. Deep point cloud regression for above-ground forest biomass estimation from airborne LiDAR. Remote Sensing of Environment 302, 2024

Patrick Bilic, Patrick Christ, Hongwei Bran Li, Eugene Vorontsov, Avi Ben-Cohen, Georgios Kaissis, Adi Szeskin, Colin Jacobs, Gabriel Efrain Humpire Mamani, Gabriel Chartrand, Fabian Lohöfer, Julian Walter Holch, Wieland Sommer, Felix Hofmann, Alexandre Hostettler, Naama Lev-Cohain, Michal Drozdzal, Michal Marianne Amitai, Refael Vivanti, Jacob Sosna, Ivan Ezhov, Anjany Sekuboyina, Fernando Navarro, Florian Kofler, Johannes C Paetzold, Suprosanna Shit, Xiaobin Hu, Jana Lipková, Markus Rempfler, Marie Piraud, Jan Kirschke, Benedikt Wiestler, Zhiheng Zhang, Christian Hülsemeyer, Marcel Beetz, Florian Ettlinger, Michela Antonelli, Woong Bae, Míriam Bellver, Lei Bi, Hao Chen, Grzegorz Chlebus, Erik B Dam, Qi Dou, Chi-Wing Fu, Bogdan Georgescu, Xavier Giró-i-Nieto, Felix Gruen, Xu Han, Pheng-Ann Heng, Jürgen Hesser, Jan Hendrik Moltz, Christian Igel, Fabian Isensee, Paul Jäger, Fucang Jia, Krishna Chaitanya Kaluva, Mahendra Khened, Ildoo Kim, Jae-Hun Kim, Sungwoong Kim, Simon Kohl, Tomasz Konopczynski, Avinash Kori, Ganapathy Krishnamurthi, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Li, John Lowengrub, Jun Ma, Klaus Maier-Hein, Kevis-Kokitsi Maninis, Hans Meine, Dorit Merhof, Akshay Pai, Mathias Perslev, Jens Petersen, Jordi Pont-Tuset, Jin Qi, Xiaojuan Qi, Oliver Rippel, Karsten Roth, Ignacio Sarasua, Andrea Schenk, Zengming Shen, Jordi Torres, Christian Wachinger, Chunliang Wang, Leon Weninger, Jianrong Wu, Daguang Xu, Xiaoping Yang, Simon Chun-Ho Yu, Yading Yuan, Miao Yue, Liping Zhang, Jorge Cardoso, Spyridon Bakas, Rickmer Braren, Volker Heinemann, Christopher Pal, An Tang, Samuel Kadoury, Luc Soler, Bram van Ginneken, Hayit Greenspan, Leo Joskowicz, and Bjoern Menze. The Liver Tumor Segmentation Benchmark (LiTS). Medical Image Analysis 84, 2023

Erik B. Dam, Arjun D. Desai, Cem M. Deniz, Haresh R. Rajamohan, Ravinder Regatte, Claudia Iriondo, Valentina Pedoia, Sharmila Majumdar, Mathias Perslev, Christian Igel, Akshay Pai, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Hasan Maqbool, Ismail Irmakci, Sang-Eun Song, Ulas Bagci, Brian Hargreaves, Garry Gold, and Akshay Chaudhari. Towards Automatic Cartilage Quantification in Clinical Trials – Continuing from the 2019 IWOAI Knee Segmentation Challenge. Osteoarthritis Imaging 3(1):100087, 2023

Jeppe Klok Due, Marianne Giørtz Pedersen, Sussie Antonsen, Joen Rommedahl, Esben Agerbo, Preben Bo Mortensen, Henrik Toft Sørensen, Jonas Færch Lotz, Laura Cabello Piqueras, Constanza Fierro, Antonia Karamolegkou, Christian Igel, Phillip Rust, Anders Søgaard, and Carsten Bøcker Pedersen. Towards more comprehensive nationwide familial aggregation studies in Denmark: The Danish Civil Registration System versus the lite Danish Multi-Generation Register. Scandinavian Journal of Public Health, 2023

Pierre Hiernaux, Bil-Assanou Hassane Issoufou, Christian Igel, Ankit Kariryaa, Moussa Kourouma, Jérôme Chave, Eric Mougin, and Patrice Savadogo. Allometric equations to estimate the dry mass of Sahel woody plants from very-high resolution satellite imagery. Forest Ecology and Management 529, 2023

Christian Igel and Stefan Oehmcke. Remember to correct the bias when using deep learning for regression! Künstliche Intelligenz 37:33-40, 2023

Lei Li, Tianfang Zhang, Stefan Oehmcke, Fabian Gieseke, and Christian Igel. BuildSeg: A General Framework for the Segmentation of Buildings. Nordic Machine Intelligence 2:1-4, 2023

Siyu Liu, Martin Brandt, Thomas Nord-Larsen, Jerome Chave, Florian Reiner, Nico Lang, Xiaoye Tong, Philippe Ciais, Christian Igel, Adrian Pascual, Juan Guerra-Hernandez, Sizhuo Li, Maurice Mugabowindekwe, Sassan Saatchi, Yuemin Yue, Zhengchao Chen and Rasmus Fensholt. The overlooked contribution of trees outside forests to tree cover and woody biomass across Europe. Science Advances 9(37), 2023

Sizhuo Li, Martin Brandt, Rasmus Fensholt, Ankit Kariryaa, Christian Igel, Fabian Gieseke, Thomas Nord-Larsen, Stefan Oehmcke, Ask Holm Carlsen, Samuli Junttila, Xiaoye Tong, Alexandre d’Aspremont, and Philippe Ciais. Deep learning enables image-based tree counting, crown segmentation and height prediction at national scale. PNAS Nexus 2(4), 2023

Florian Reiner, Martin Brandt, Xiaoye Tong, David Skole, Ankit Kariryaa, Philippe Ciais, Andrew Davies, Pierre Hiernaux, Jerome Chave, Maurice Mugabowindekwe, Christian Igel, Stefan Oehmcke, Fabian Gieseke, Sizhuo Li, Siyu Liu, Sassan S. Saatchi, Peter Boucher, Jenia Singh, Simon Taugourdeau, Morgane Dendoncker, Xiao-Peng Song, Ole Mertz, Compton Tucker, and Rasmus Fensholt. More than one quarter of Africa’s tree cover found outside areas previously classified as forest. Nature Communications 14, 2023

Compton Tucker, Martin Brandt, Pierre Hiernaux, Ankit Kariryaa, Kjeld Rasmussen, and Jennifer Small, Christian Igel, Florian Reiner, Katherine Melocik, Jesse Meyer, Scott Sinno, Eric Romero, Erin Glennie, Yasmin Fitts, August Morin, Jorge Pinzon, Devin McClain, Paul Morin, Claire Porter, Shane Loeffle, Laurent Kergoat, Bil-Assanou Issoufou, Patrice Savadogo, Jean-Pierre Wigneron, Benjamin Poulter, Philippe Ciais, Robert Kaufmann, Ranga Myneni, Sassan Saatchi, and Rasmus Fensholt. Sub-continental scale carbon stocks of individual trees in African drylands. Nature 615:80-86, 2023

Philip Enevoldsen, Christian Gundersen, Nico Lang, Serge Belongie, and Christian Igel. Familiarity-Based Open-Set Recognition Under Adversarial Attacks. 2nd Workshop and Challenges for Out-of-Distribution Generalization in Computer Vision (OOD-CV), 2023

Hui Zhang, Ankit Kariryaa, Venkanna Babu Guthula, Christian Igel, and Stefan Oehmcke. Predicting urban tree cover from incomplete point labels and limited background information. UrbanAI '23: Proceedings of the 1st ACM SIGSPATIAL International Workshop on Advances in Urban-AI, ACM, 2023.

Rasmus Kær Jørgensen, Oliver Brandt, Mareike Hartmann, Xiang Dai, Christian Igel, and Desmond Elliott. MultiFin: A Dataset for Multilingual Financial NLP. Findings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL Findings), 2023

Bobby Lo, ZhuoYuan Liu, Flemming Bendtsen, Christian Igel, Ida Vind, and Johan Burisch. High Accuracy in Classifying Endoscopic Severity in Ulcerative Colitis Using Convolutional Neural Networks. American Journal of Gastroenterology 117(10):1648-1654, 2022

Abdelrahman Mohamed, Hung-yi Lee, Lasse Borgholt, Jakob D. Havtorn, Joakim Edin, Christian Igel, Katrin Kirchhoff, Shang-Wen Li, Karen Livescu, Lars Maaløe, Tara N. Sainath, Shinji Watanabe. Self-Supervised Speech Representation Learning: A Review. IEEE Journal of Selected Topics in Signal Processing, 16(6):1179–1210, 2022

Maurice Mugabowindekwe, Martin Brandt, Jerome Chave, Florian Reiner, David Skole, Ankit Kariryaa, Christian Igel, Pierre Hiernaux, Philippe Ciais, Ole Mertz, Xiaoye Tong, Sizhuo Li, Gaspard Rwanyiziri, Thaulin Dushimiyimana, Alain Ndoli, Valens Uwizeyimana, Jens-Peter Lillesø, Fabian Gieseke, Compton Tucker, Sassan S. Saatchi, and Rasmus Fensholt. Nation-wide mapping of tree-level aboveground carbon stocks in Rwanda. Nature Climate Change 13:91-97, 2022

Mathias Perslev, Akshay Pai, Jon Runhaar, Christian Igel, and Erik B. Dam. Cross-Cohort Automatic Knee MRI Segmentation with Multi-Planar U-Nets. Journal of Magnetic Resonance Imaging 55(6):1650-1663, 2022

Jaime Caballer Revenga, Katerina Trepekli, Stefan Oehmcke, Rasmus Jensen, Lei Li, Christian Igel, Fabian Cristian Gieseke, Thomas Friborg. Aboveground biomass prediction in croplands at sub-meter resolution based on UAV-LiDAR and machine learning methods. Remote Sensing 14(16):3912, 2022

Lasse Borgholt, Jakob D. Havtorn, Joakim Edin, Lars Maaløe, and Christian Igel. A Brief Overview of Unsupervised Neural Speech Representation Learning. The 2nd Workshop on Self-supervised Learning for Audio and Speech Processing (AAAI-SAS-2022), 2022

Pengfei Diao, Akshay Pai, Christian Igel, and Christian Hedeager Krag. Histogram-based unsupervised domain adaptation for medical image classification. In L. Wang, Q. Dou, P. T. Fletcher, S. Speidel, and S. Li, eds.: Medical Image Computing and Computer Assisted Intervention (MICCAI), pp. 755–764, LNCS 13437, Springer, 2022

Constanza Fierro, Laura Cabello Piqueras, Jonas Lotz, Philip Rust, Joen Rommedahl, Jeppe Klok Due, Christian Igel, Desmond Elliott, Carsten Bøcker Pedersen, Israfel Salazar and Anders Søgaard. Date Recognition in Historical Parish Records. International Conference on Frontiers in Handwriting Recognition (ICFHR), pp. 49–64, LNCS 13639, Springer, 2022

Thorben Hellweg, Stefan Oehmcke, Ankit Kariryaa, Fabian Gieseke, and Christian Igel. Ensemble Learning for Semantic Segmentation of Ancient Maya Architectures. In D. Kocev, N. Simidjievski, A. Kostovska, I. Dimitrovski, and Žiga Kokalj, eds.: Discover the Mysteries of the Maya, pp. 13–19. Jožef Stefan Institute, Jamova cesta 39, 1000 Ljubljana, Slovenia, 2022

Rasmus Kær Jørgensen, Fiammetta Caccavale, Christian Igel, and Anders Søgaard. Are Multilingual Sentiment Models Equally Right for the Right Reasons? BlackboxNLP Workshop at EMNLP 2022, 2022

Stephan Sloth Lorenzen, Christian Igel, and Mads Nielsen. Information Bottleneck: Exact Analysis of (Quantized) Neural Networks. In: International Conference on Learning Representations (ICLR), 2022

Stefan Oehmcke, Lei Li, Jaime Revenga, Thomas Nord-Larsen, Katerina Trepekli, Fabian Gieseke, Christian Igel. Deep Learning Based 3D Point Cloud Regression for Estimating Forest Biomass. In: International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL), ACM, 2022

Tianfang Zhang, Lei Li, Christian Igel, Stefan Oehmcke, Fabian Gieseke, and Zhenming Peng. LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing. In: IEEE International Conference on Computer and Communications (ICCC), IEEE, 2022

Arjun D. Desai, Francesco Caliva, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew Torigian, Jutta Ellerman, Mehmet Akcakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O'Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry E. Gold, Brian A Hargreaves, Valentina Pedoia, and Akshay S. Chaudhari. The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset. Radiology: Artificial Intelligence 3:e200078, 2021

Espen Jimenez-Solem, Tonny S. Petersen, Casper Hansen, Christian Hansen, Christina Lioma, Christian Igel, Wouter Boomsma, Oswin Krause, Stephan Lorenzen, Raghavendra Selvan, Janne Petersen, Martin Erik Nyeland, Mikkel Zöllner Ankarfeldt, Gert Mehl Virenfeldt, Matilde WintherJensen, Allan Linneberg, Mostafa Mediphour Ghazi, Nicki Detlefsen, Andreas Lauritzen, Abraham George Smith, Marleen de Bruijne, Bulat Ibragimov, Jens Petersen, Martin Lillholm, Jon Middleton, Stine Hasling Mogensen, Hans-Christian Thorsen-Meyer, Anders Perner, Marie Helleberg, Benjamin Skov Kaas-Hansen, Mikkel Bonde, Alexander Bonde, Akshay Pai, Mads Nielsen, and Martin Sillesen. Developing and Validating COVID-19 Adverse Outcome Risk Prediction Models From a Bi-national European Cohort of 5594 Patients. Scientific Reports 11, 3246, 2021

Rasmus Kær Jørgensen and Christian Igel. Machine learning for financial transaction classification across companies using character-level word embeddings of text fields. Intelligent Systems in Accounting, Finance and Management 28(3), pages 159-172, 2021

Mathias Perslev, Sune Darkner, Lykke Kempfner, Miki Nikolic, Poul Jørgen Jennum, and Christian Igel. U-Sleep: Resilient High-Frequency Sleep Staging. npj Digital Medicine 4, 2021

Stephan Sloth Lorenzen, Mads Nielsen, Espen Jimenez-Solem, Tonny Studsgaard Petersen, Anders Perner, Hans-Christian Thorsen-Meyer, Christian Igel, and Martin Sillesen. Using Machine Learing for Predicting Intensive Care Unit Resource Use During the Covid-19 Pandemic in Denmark. Scientific Reports 11:18959, 2021

Christian Igel. Data, Knowledge, and Computation. Künstliche Intelligenz, 2021 (editorial)

Lasse Borgholt, Tycho M. S. Tax, Jakob D. Havtorn, Lars Maaløe, Christian Igel. On scaling contrastive representations for low resource speech recognition. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 3885-3889, 2021 preprint

Kai Brügge, Asja Fischer, and Christian Igel. On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. International Conference on Artificial Intelligence and Statistics (AISTATS), Proceedings of Machine Learning Research 130, pp. 469-477, 2021

Yi-Shan Wu, Andrés R. Masegosa, Stephan S. Lorenzen, Christian Igel, and Yevgeny Seldin. Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote. Advances in Neural Information Processing Systems (NeurIPS), 2021

Martin Brandt, Compton J. Tucker, Ankit Kariryaa, Kjeld Rasmussen, Christin Abel, Jennifer Small, Jerome Chave, Laura Vang Rasmussen, Pierre Hiernaux, Abdoul Aziz Diouf, Laurent Kergoat, Ole Mertz, Christian Igel, Fabian Gieseke, Johannes Schöning, Sizhuo Li, Katherine Melocik, Jesse Meyer, Scott Sinno, Eric Romero, Erin Glennie, Amandine Montagu, Morgane Dendoncker, and Rasmus Fensholt. An unexpectedly large count of trees in the western Sahara and Sahel. Nature, 2020 popular science summary

Oswin Krause, Asja Fischer, and Christian Igel. Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines. Artificial Intelligence 278, 2020

Lasse Borgholt, Jakob Drachmann Havtorn, Željko Agić, Anders Søgaard, Lars Maaløe, and Christian Igel. Do End-to-End Speech Recognition Models Care About Context? Interspeech 2020, 2020

Steffen Czolbe, Oswin Krause, Ingemar Cox, and Christian Igel. A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model. Advances in Neural Information Processing Systems (NeurIPS), 2020 source code video

Ürün Dogan, Aniket Anand Deshmukh, Marcin Machura, and Christian Igel. Label-similarity Curriculum Learning. European Conference on Computer Vision (ECCV), LNCS 12374, pp. 174-190, Springer-Verlag, 2020

Oswin Krause, Asja Fischer, and Christian Igel. Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract). International Joint Conferences on Artificial Intelligence (IJCAI), pp. 5045-5049, 2020

Andrés R. Masegosa, Stephan S. Lorenzen, Christian Igel, and Yevgeny Seldin. Second Order PAC-Bayesian Bounds for the Weighted Majority Vote. Advances in Neural Information Processing Systems (NeurIPS), 2020

Stephan S. Lorenzen, Christian Igel, and Yevgeny Seldin. On PAC-Bayesian Bounds for Random Forests. Machine Learning 108(8-9), pp. 1503–1522, 2019

Saeed Shakibfar, Oswin Krause, Casper Lund-Andersen, Filip Strycko, Jonas Moll, Tariq Osman Andersen, Helen Høgh Petersen, Jesper Hastrup Svendsen, and Christian Igel. Impact of device programming on the success of the first anti-tachycardia pacing therapy: An anonymized large-scale study. PLOS ONE 14(8): e0219533, 2019

Saeed Shakibfar, Oswin Krause, Casper Lund-Andersen, Alfonso Aranda Hernandez, Jonas Moll, Tariq Osman Andersen, Jesper Hastrup Svendsen, Helen Høgh Petersen, and Christian Igel. Predicting Electrical Storms by Remote Monitoring of Implantable Cardioverter Defibrillator Patients Using Machine Learning. EP Europace 21(2), pp. 268-274, 2019

Fabian Gieseke, Cosmin Eugen Oancea, Ashish Mahabal, Christian Igel, and Tom Heskes. Bigger Buffer k-d Trees on Multi-Many-Core Systems. In: Senger H. et al., eds.: High Performance Computing for Computational Science (VECPAR 2018), LNCS 11333, pp. 202-214,Springer-Verlag, 2019 source code

Thorbjørn Louring Koch, Mathias Perslev, Christian Igel, and Sami Sebastian Brandt. Accurate Segmentation of Dental Panoramic Radiographs with U-Nets. In: IEEE International Symposium on Biomedical Imaging (ISBI), pp. 15-19, IEEE Press, 2019

Mauricio Orbes-Arteaga, Jorge Cardoso, Lauge Sørensen, Christian Igel, Sebastien Ourselin, Marc Modat, Mads Nielsen, and Akshay Pai. Knowledge distillation for semi-supervised domain adaptation. In: Machine Learning in Clinical Neuroimaging (MLCN 2019), LNCS 11796, pp. 68-76, 2019

Mauricio Orbes-Arteaga, Lauge Sørensen, Jorge Cardoso, Marc Modat, Sebastien Ourselin, Stefan Sommer, Mads Nielsen, Christian Igel, and Akshay Pai. PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation. In: Medical Imaging 2019: Image Processing, Proceedings of SPIE 10949, SPIE, 2019

Mathias Perslev, Michael Hejselbak Jensen, Sune Darkner, Poul Jørgen Jennum, and Christian Igel. U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging. Advances in Neural Information Processing Systems (NeurIPS 2019), pp. 4417-4428, 2019 source code

Mathias Perslev, Erik Dam, Akshay Pai, and Christian Igel. One Network To Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation. In: Medical Image Computing and Computer Assisted Intervention (MICCAI), LNCS 11765, pp. 30-38, Springer, 2019 source code

Oswin Krause, Asja Fischer and Christian Igel. Population-Contrastive-Divergence: Does Consistency help with RBM training? Pattern Recognition Letters 102, pp. 1-7, 2018

Dídac R. Arbonès, Nataliia Y. Sergiienko, Boyin Ding, Oswin Krause, Christian Igel and Markus Wagner. Sparse Incomplete LU-decomposition for Wave Farm Designs under Realistic Conditions. Parallel Problem Solving from Nature (PPSN), LNCS, Springer-Verlag, 2018

Ciprian Florescu and Christian Igel. Resilient Backpropagation (Rprop) for Batch-learning in TensorFlow. 6th International Conference on Learning Representations Workshop Track (ICLR 2018 Workshop Track) 2018

Fabian Gieseke and Christian Igel. Training Big Random Forests with Little Resources. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 1445-1454, ACM Press, 2018 source code

Jan Kremer, Fei Sha, and Christian Igel. Robust Active Label Correction. International Conference on Artificial Intelligence and Statistics (AISTATS), Proceedings of Machine Learning Research 84, 2018

Fabian Gieseke, Kai Polsterer, Ashish Mahabal, Christian Igel, and Tom Heskes. Massively-Parallel Best Subset Selection for Ordinary Least-Squares Regression. IEEE Symposium Series on Computational Intelligence (SSCI 2017), IEEE Press, 2018

Mathias Perslev, Akshay Pai, Christian Igel, and Erik Dam. Knee Segmentation by Multiplanar Deep Learning Network – with data from OAI. International Workshop on Osteoarthritis Imaging, 2018

Fabian Gieseke, Cosmin Oancea, and Christian Igel. bufferkdtree: A Python Library for Massive Nearest Neighbor Queries on Multi-Many-Core Devices. Knowledge-Based Systems 120, pp. 1-3, 2017 source code

Jan Kremer, Kristoffer Stensbo-Smidt, Fabian Gieseke, Kim Steenstrup Pedersen, and Christian Igel. Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. IEEE Intelligent Systems 32(2), pp. 16-22, 2017

Marc Schlipsing, Jan Salmen, Marc Philipp Tschentscher, and Christian Igel. Adaptive Pattern Recognition in Real-time Video-based Soccer Analysis. Journal of Real-Time Image Processing 13(2), pp. 345-361, 2017

Lauge Sørensen, Christian Igel, Akshay Pai, Ioana Balas, Cecilie Anker, Martin Lillholm, and Mads Nielsen. Differential diagnosis of mild cognitive impairment and Alzheimer's disease using structural MRI cortical thickness, hippocampal shape, hippocampal texture, and volumetry. NeuroImage: Clinical 13, pp. 470-482, 2017

Akshay Pai, Yuan-Ching Teng, Joseph Blair, Michiel Kallenberg, Erik B. Dam, Stefan Sommer, Christian Igel, and Mads Nielsen. Characterisation of errors in deep learning-based brain MRI segmentation. In S. K. Zhou, H. Greenspan, and D. Shen, eds.: Deep Learning for Medical Image Analysis, Chapter 10, pp. 223–242, Academic Press, 2017

Oswin Krause, Christian Igel, and Tobias Glasmachers. Qualitative and Quantitative Assessment of Step Size Adaptation Rules. Foundations of Genetic Algorithms (FOGA 2017), pp. 139-148, ACM Press, 2017

Niklas Thiemann, Christian Igel, Olivier Wintenberger, and Yevgeny Seldin. A Strongly Quasiconvex PAC-Bayesian Bound. In S. Hanneke and L. Reyzin, eds.: Algorithmic Learning Theory (ALT), Proceedings of Machine Learning Research 76, pp. 466-492, 2017

Ürün Dogan, Tobias Glasmachers, and Christian Igel. A Unified View on Multi-class Support Vector Classification. Journal of Machine Learning Research 17(45), pp. 1-32, 2016

Michiel Kallenberg, Kersten Petersen, Mads Nielsen, Andrew Y. Ng, Pengfei Diao, Christian Igel, Celine M. Vachon, Katharina Holland, Rikke Rass Winkel, Nico Karssemeijer, and Martin Lillholm. Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring. IEEE Transactions on Medical Imaging 35(5), pp. 1322-1331, 2016

Kristoffer Stensbo-Smidt, Fabian Gieseke, Christian Igel, Andrew Zirm, and Kim Steenstrup Pedersen. Sacrificing Information for the Greater Good: How to Select Photometric Bands for Optimal Accuracy. Monthly Notices of the Royal Astronomical Society 464(3), pp. 2577-2596, 2016

Lauge Sørensen, Christian Igel, Naja Liv Hansen, Merete Osler, Martin Lauritzen, Egill Rostrup, and Mads Nielsen. Early detection of Alzheimer’s disease using MRI hippocampal texture. Human Brain Mapping 37, pp. 1148-1161, 2016

Lars Lau Raket, Britta Grimme, Gregor Schöner, Christian Igel, and Bo Markussen. Separating timing, movement conditions and individual differences in the analysis of human movement. PLoS Computational Biology 12(9), 2016

Matthias Tuma, Valdemar Rørbech, Mark Prior, and Christian Igel. Integrated optimization of long-range underwater signal detection, feature extraction, and classification for nuclear treaty monitoring. IEEE Transactions on Geoscience and Remote Sensing 54(6), pp. 3649-3659, 2016

Christian Igel. Evolutionary kernel learning. Encyclopedia of Machine Learning and Data Mining, Springer, 2016

Michiel Kallenberg, Mads Nielsen, Nico Karssemeijer, Christian Igel, and Martin Lillholm. Learning Density Independent Texture Features. In A. Tingberg, K. Lång, and P. Timberg, eds.: Breast Imaging, LNCS 9699, pp. 299-306, Springer-Verlag, 2016

Oswin Krause, Dídac R. Arbonès, and Christian Igel. CMA-ES with Optimal Covariance Update and Storage Complexity. Advances in Neural Information Processing Systems (NIPS), supplement, 2016

Oswin Krause, Tobias Glasmachers, and Christian Igel. Multi-objective Optimization with Unbounded Solution Sets. NIPS Workshop on Bayesian Optimization (BayesOpt 2016), submission, 2016

Oswin Krause, Tobias Glasmachers, Nikolaus Hansen, and Christian Igel. Unbounded population MO-CMA-ES for the bi-objective BBOB test suite. In Companion of the Eighteens International Conference on Genetic and Evolutionary Computation (GECCO 2016): BBOB-2016 Workshop, 2016, pp. 1177-1184, ACM, 2016

Kai Lars Polsterer, Fabian Gieseke, Christian Igel, Bernd Doser, and Nikos Gianniotis. Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs. 24th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2016), pp. 405-410, Belgium: i6doc.com, 2016

Asja Fischer and Christian Igel. A Bound for the Convergence Rate of Parallel Tempering for Sampling Restricted Boltzmann Machines. Theoretical Computer Science 598, pp. 102–117, 2015

Jan Kremer, Fabian Gieseke, Kim Steenstrup Pedersen, and Christian Igel. Nearest Neighbor Density Ratio Estimation for Large-Scale Applications in Astronomy. Astronomy and Computing 12, pp. 67-72, 2015 source code

Søren Frejstrup Maibing and Christian Igel. Computational Complexity of Linear Large Margin Classification With Ramp Loss. JMLR W&CP 38 (AISTATS), pp. 259-267, 2015

Kai Lars Polsterer, Fabian Gieseke, and Christian Igel. Automatic classification of galaxies via machine learning techniques: Parallelized Rotation/Flipping INvariant Kohonen Maps (PINK). In A. R. Taylor and E. Rosolowsky, eds.: Astronomical Data Analysis Software and Systems (ADASS XXVI), pp. 81-86. Astronomical Society of the Pacific, ASP Conference Series 495, 2015 Best Poster Award

Nicolae-Bogdan Şara, Rasmus Halland, Christian Igel, and Stephen Alstrup. High-school dropout prediction using machine learning: A Danish large-scale study. In M. Verleysen, ed.: 23th European Symposium on Artificial Neural Networks (ESANN 2015). i6doc.com, 2015

Oswin Krause and Christian Igel. A More Efficient Rank-one Covariance Matrix Update for Evolution Strategies. In J. He, T. Jansen, G. Ochoa, and C. Zarges, eds.: Foundations of Genetic Algorithms (FOGA 2015), pp. 129-136, ACM Press, 2015

Oswin Krause, Asja Fischer and Christian Igel. Population Monte Carlo Meets Contrastive Divergence Learning. In B. Hammer and M. Martinetz and T. Villmann, eds.: New Challenges in Neural Computation (NC²), Machine Learning Reports 03/2015, pp. 93-94, 2015

Asja Fischer and Christian Igel. Training Restricted Boltzmann Machines: An Introduction. Pattern Recognition 47, pp. 25-39, 2014

Jan Kremer, Kim Steenstrup Pedersen, and Christian Igel. Active Learning with Support Vector Machines. WIREs Data Mining and Knowledge Discovery 4(4), pp. 313-326, 2014

Fabian Gieseke, Justin Heinermann, Cosmin Oancea, and Christian Igel. Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. JMLR W&CP 32 (ICML), pp. 172-180, 2014 source code

Christian Igel. No Free Lunch Theorems: Limitations and Perspectives of Metaheuristics. In Y. Borenstein and A. Moraglio, eds.: Theory and Principled Methods for the Design of Metaheuristics, pp. 1-23, Springer-Verlag, 2014

Dídac R. Arbonès, Henrik G. Jensen, Annika Loft, Per Munck af Rosenschöld, Anders Elias Hansen, Christian Igel, and Sune Darkner. Automatic FDG-PET-based tumor and metastatic lymph node segmentation in cervical cancer. In: Proc. SPIE 9034, Medical Imaging 2014: Image Processing, 903441, 2014

Fabian Gieseke, Kai Lars Polsterer, Cosmin E. Oancea, and Christian Igel. Speedy Greedy Feature Selection: Better Redshift Estimation via Massive Parallism. In M. Verleysen, ed.: 22th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2014), pp. 87-92, Belgium: i6doc.com, 2014

Kai Lars Polsterer, Fabian Gieseke, Christian Igel, and Tomotsugu Goto. Improving the Performance of Photometric Regression Models via Massive Parallel Feature Selection. In N. Manset and P. Forshay, eds.: 23rd Annual Astronomical Data Analysis Software and Systems Conference (ADASS XXIII), pp. 425-428, ASP Conference Series 485, 2014

Lauge Sørensen, Akshay Pai, Cecilie Anker, Ioana Balas, Martin Lillholm, Christian Igel, and Mads Nielsen. Dementia diagnosis using MRI cortical thickness, shape, texture, and volumetry. In E. E. Bron, S. Klein, M. Smits, J. C. van Swieten, and W. J. Niessen, eds.: Medical Image Computing and Computer Assisted Intervention (MICCAI): CADDementia Workshop, 2014. 1st and 2nd rank in the CADDementia Grand Challenge

Karl Bringmann, Tobias Friedrich, Christian Igel, and Thomas Voß. Speeding Up Many-Objective Optimization by Monte Carlo Approximations. Artificial Intelligence 204, pp. 22-29, 2013

Kai Brügge, Asja Fischer, and Christian Igel. The flip-the-state transition operator for restricted Boltzmann machines. Machine Learning 13, pp. 53-69, 2013

Fabian Gieseke, Christian Igel, and Tapio Pahikkala. Polynomial runtime bounds for fixed-rank unsupervised least-squares classification. JMLR W&CP 29 (ACML), pp. 62-71, 2013

Christian Igel. A Note on Generalization Loss When Evolving Adaptive Pattern Recognition Systems. IEEE Transactions on Evolutionary Computation 17(3), pp. 345-352, 2013

Oswin Krause, Asja Fischer, Tobias Glasmachers, and Christian Igel. Approximation properties of DBNs with binary hidden units and real-valued visible units. JMLR W&CP 28 (ICML), pp. 419–426, 2013

Joselene Marques, Christian Igel, Martin Lillholm, and Erik B. Dam. Linear feature selection in texture analysis. Machine Vision and Applications 24, pp. 1435-1444, 2013

Marc Schlipsing, Jan Salmen, and Christian Igel. Echtzeit-Videoanalyse im Fußball - Entwurf eines Live-Systems zum Spieler-Tracking. Künstliche Intelligenz 27(3), pp 235-240, 2013

Søren Dahlgaard, Christian Igel, and Mikkel Thorup. Nearest Neighbor Classification Using Bottom-k Sketches. IEEE International Conference on Big Data 2013, pp. 28-34, IEEE Press, 2013

Sebastian Houben, Johannes Stallkamp, Jan Salmen, Marc Schlipsing, and Christian Igel. Detection of Traffic Signs in Real-World Images: The German Traffic Sign Detection Benchmark. International Joint Conference on Neural Networks (IJCNN 2013), pp. 715-722, IEEE Press, 2013 data

Kim Steenstrup Pedersen, Kristoffer Stensbo-Smidt, Andrew Zirm, and Christian Igel. Shape Index Descriptors Applied to Texture-Based Galaxy Analysis. International Conference on Computer Vision (ICCV), pp 2440-2447, IEEE Press, 2013

Kristoffer Stensbo-Smidt, Christian Igel, Andrew Zirm, and Kim Steenstrup Pedersen. Nearest Neighbour Regression Outperforms Model-based Prediction of Specific Star Formation Rate. IEEE International Conference on Big Data 2013, pp. 141-144, IEEE Press, 2013

Adhish Prasoon, Kersten Petersen, Christian Igel, Francois Lauze, Erik Dam, and Mads Nielsen. Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network. In: Medical Image Computing and Computer Assisted Intervention (MICCAI 2013), LNCS 8150, pp 246-253, Springer-Verlag, 2013

Adhish Prasoon, Christian Igel, Marco Loog, Francois Lauze, Erik Dam, and Mads Nielsen. Femoral Cartilage Segmentation in Knee MRI Scans Using Two Stage Voxel Classification. In: 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp 5469-5472, IEEE Press, 2012 note

Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel. Man vs. Computer: Benchmarking Machine Learning Algorithms for Traffic Sign Recognition. Neural Networks 32, pp. 323-332, 2012 data

Christian Igel. Learning ∈ Artificial Intelligence ∩ Cognitive Technologies ∩ Neural Computation ∩ ... Künstliche Intelligenz 26(3), pp. 209-212, 2012 (editorial)

Oliver Kramer, Christian Igel, and Günter Rudolph. Evolutionary Kernel Machines. Evolutionary Intelligence 5(3), pp. 151-152, 2012 (guest editorial)

Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel. Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition. IEEE Transactions on Transportation Systems 13(4), pp. 1481-1481, 2012 (guest editorial)

Matthias Tuma, Christian Igel, and Mark Prior. Hydroacoustic Signal Classification Using Support Vector Machines. In C. H. Chen, ed.: Signal and Image Processing for Remote Sensing, 2nd edition, pp. 37-56, CRC Press, 2012

Chen Chen, Lauge Sørensen, Francois Lauze, Christian Igel, Marco Loog, Aasa Feragen, Marleen de Bruijne, and Mads Nielsen. Towards exaggerated emphysema stereotypes. In: SPIE Medical Imaging 2012: Image Processing. Proceedings of SPIE 8315, 83150Q, 2012

Ürün Dogan, Tobias Glasmachers, and Christian Igel. A Note on Extending Generalization Bounds for Binary Large-margin Classifiers to Multiple Classes. In P. A. Flach, T. De Bie, and N. Cristianini, eds.: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2012), LNCS 7523, pp.122-129, Springer-Verlag, 2012

Asja Fischer and Christian Igel. An Introduction to Restricted Boltzmann Machines. In L. Alvarez, M. Mejail, L. Gomez, and J. Jacobo, eds.: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications (CIARP 2012), LNCS 7441, pp. 14-36, Springer-Verlag, 2012

Adhish Prasoon, Christian Igel, Marco Loog, Francois Lauze, Erik Dam, and Mads Nielsen. Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage. In: SPIE Medical Imaging 2012: Image Processing. Proceedings of SPIE 8314, 83144V, 2012

Ürün Dogan, Tobias Glasmachers, and Christian Igel. Turning Binary Large-margin Bounds into Multi-class Bounds. In A. Gretton, Z. Harchaoui, and B. Sriperumbudur, organizers: ICML 2012 Workshop on RKHS and kernel-based methods, 2012

Holger Blume, Bernd Bischl, Martin Botteck, Christian Igel, Rainer Martin, Günther Rötter, Günter Rudolph, Wolfgang Theimer, Igor Vatolkin, and Claus Weihs. Huge Music Archives on Mobile Devices. IEEE Signal Processing Magazine, 28(4), pp. 24-39, 2011

Asja Fischer and Christian Igel. Bounding the Bias of Contrastive Divergence Learning. Neural Computation 23, pp. 664-673, 2011

Chen Chen, Francois Lauze, Christian Igel, Aasa Feragen, Marco Loog, and Mads Nielsen. Towards exaggerated image stereotypes. In: Asian Conference on Pattern Recognition (ACPR 2011), pp. 422-426, IEEE Press, 2011

Asja Fischer and Christian Igel. Training RBMs Based on the Signs of the CD Approximation of the Log-likelihood Derivatives. In M. Verleysen, ed.: 19th European Symposium on Artificial Neural Networks (ESANN 2011), pp. 495-500, Belgium: d-side publications, 2011

Tobias Friedrich, Karl Bringmann, Thomas Voß, and Christian Igel. The Logarithmic Hypervolume Indicator. In H.G. Beyer and W. B. Langdon, eds.: Foundations of Genetic Algorithms (FOGA 2011), pp. 81-92, ACM Press, 2011

Verena Heidrich-Meisner and Christian Igel. Non-linearly Increasing Resampling in Racing Algorithms. In M. Verleysen, ed.: 19th European Symposium on Artificial Neural Networks (ESANN 2011), pp. 465-470, Belgium: d-side publications, 2011

Jan Salmen, Lukas Caup, and Christian Igel. Real-time Estimation of Optical Flow Based on Optimized Haar Wavelet Features. In R. H. C. Takahashi, K. Deb, E. F. Wanner and S. Greco, eds.: Sixth International Conference on Evolutionary Multi-Criterion Optimization (EMO 2011), LNCS 6576, pp. 448-461, Springer-Verlag, 2011

Johannes Stallkamp, Marc Schlipsing, Jan Salmen, and Christian Igel. The German Traffic Sign Recognition Benchmark: A Multi-class Classification Competition. International Joint Conference on Neural Networks (IJCNN 2011), pp. 1453-1460, IEEE Press, 2011 data

Matthias Tuma and Christian Igel. Improved Working Set Selection for LaRank. In A. Berciano et al., eds.: 14th International Conference on Computer Analysis of Images and Patterns (CAIP 2011), LNCS 6854, pp. 327-334, Springer-Verlag, 2011

Tobias Glasmachers and Christian Igel. Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters. IEEE Transactions on Pattern Analysis and Machine Intelligence 32(8), pp. 1522-1528, 2010 source code

Jan Salmen, Marc Schlipsing, and Christian Igel. Efficient Update of the Covariance Matrix Inverse in Iterated Linear Discriminant Analysis. Pattern Recognition Letters 31(1), pp. 1903-1907, 2010

Valentin Markounikau, Christian Igel, Amiram Grinvald, and Dirk Jancke. Dynamic Neural Field Model of Mesoscopic Cortical Activity Captured with Voltage-sensitive Dye Imaging. PLoS Computational Biology 6(9), 2010

Benjamin Roeschies and Christian Igel. Structure Optimization of Reservoir Networks. Logic Journal of the IGPL 18(5), pp. 635-669, 2010

Rolf P. Würtz, Kirstie L. Bellman, Hartmut Schmeck, and Christian Igel. Special Issue on Organic Computing. ACM Transactions Autonomous and Adaptive Systems, (3), pp. 1-3, 2010 (guest editorial)

Christian Igel. Evolutionary Kernel Learning. In C. Sammut and G. I. Webb, eds.: Encyclopedia of Machine Learning, Springer-Verlag, 2010

Asja Fischer and Christian Igel. Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines. In K. Diamantaras, W. Duch, and L. S. Iliadis, eds.: International Conference on Artificial Neural Networks (ICANN 2010), LNCS 6354, pp. 208-217, Springer-Verlag, 2010

Asja Fischer and Christian Igel. Challenges in Training Restricted Boltzmann Machines. In B. Hammer and T. Villmann, eds.: New Challenges in Neural Computation (NC²), Machine Learning Reports 04/2010, pp. 11–24, 2010

Verena Heidrich-Meisner and Christian Igel. Direct policy search: Intrinsic versus extrinsic perturbations. In B. Hammer and T. Villmann, eds.: New Challenges in Neural Computation (NC²), Machine Learning Reports 04/2010, pp. 33–39, 2010

Matthias Tuma, Christian Igel, and Mark Prior. Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets. In: International Conference on Pattern Recognition (ICPR 2010), 2010

Thomas Voß, Heike Trautmann, and Christian Igel. New Uncertainty Handling Strategies in Multi-Objective Evolutionary Optimization. Parallel Problem Solving from Nature (PPSN XI), LNCS, Springer-Verlag, 2010

Thomas Voß, Tobias Friedrich, Karl Bringmann, and Christian Igel. Scaling Up Indicator-based MOEAs by Approximating the Least Hypervolume Contributor: A Preliminary Study. In N. Beume and D. Brockhoff, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010): Workshop on Theoretical Aspects of Evolutionary Multiobjective Optimization, pp. 1975-1978, ACM Press, 2010

Thomas Voß, Nikolaus Hansen, and Christian Igel. Improved Step Size Adaptation for the MO-CMA-ES. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2010), pp. 487-494, ACM Press, 2010

Verena Heidrich-Meisner and Christian Igel. Neuroevolution Strategies for Episodic Reinforcement Learning. Journal of Algorithms 64(4), pp. 152-168, 2009

Christian Igel. Service: Reinforcement Learning. Künstliche Intelligenz 09(3), p. 44, 2009

Christian Igel. Reinforcement Learning. Künstliche Intelligenz 09(3), p. 4, 2009 (guest editorial)

Thorsten Suttorp, Nikolaus Hansen, and Christian Igel. Efficient Covariance Matrix Update for Variable Metric Evolution Strategies. Machine Learning 75, pp. 167-197, 2009 source code

Julian Togelius, Tom Schaul, Daan Wierstra, Christian Igel, Faustino Gomez, and Jürgen Schmidhuber. Ontogenetic and Phylogenetic Reinforcement Learning. Künstliche Intelligenz 09(3), pp. 30-33, 2009

Susanne Winter, Ioannis Pechlivanis, Claudia Dekomien, Bernhard Brendel, Christian Igel, and Kirsten Schmieder. Toward Registration of 3D Ultrasound and CT Images of the Spine in Clinical Praxis: Design and Evaluation of a Data Acquisition Protocol. Ultrasound in Medicine and Biology 35(11), pp. 1773-1782, 2009, doi:10.1016/j.ultrasmedbio.2009.06.1089

Asja Fischer and Christian Igel. Contrastive Divergence Learning May Diverge When Training Restricted Boltzmann Machines. Frontiers in Computational Neuroscience. Conference Abstract: Bernstein Conference on Computational Neuroscience (BCCN 2009), 2009, doi:10.3389/conf.neuro.10.2009.14.121

Verena Heidrich-Meisner and Christian Igel. Hoeffding and Bernstein Races for Selecting Policies in Evolutionary Direct Policy Search. In L. Bottou and M. Littman, eds.: Proceedings of the International Conference on Machine Learning (ICML 2009), pp. 401-408, 2009

Verena Heidrich-Meisner and Christian Igel. Uncertainty Handling CMA-ES for Reinforcement Learning. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2009), pp. 1211-1218, ACM Press, 2009

Verena Heidrich-Meisner and Christian Igel. Variable-metric Evolution Strategies for Direct Policy Search. In: Multidisciplinary Symposium on Reinforcement Learning (MSRL 2009), 2009

Christian Igel and Tobias Glasmachers. Second-order SMO for SVM Online and Active Learning. In: 23rd European Conference on Operational Research (EURO 2009), 2009

Valentin Markounikau, Christian Igel, and Dirk Jancke. A Mesoscopic Model of VSD Dynamics Observed in Visual Cortex Induced by Flashed and Moving Stimuli. Frontiers in Computational Neuroscience. Conference Abstract: Bernstein Conference on Computational Neuroscience (BCCN 2009), 2009, doi: 10.3389/conf.neuro.10.2009.14.064

Matthias Tuma and Christian Igel. Kernel-based Machine Learning Techniques for Hydroacoustic Signal Classification. International Scientific Studies Conference (ISS 2009), 2009

Thomas Voß, Nikolaus Hansen, and Christian Igel. Recombination for Learning Strategy Parameters in the MO-CMA-ES. In M. Ehrgott, C. Fonseca, X. Gandibleux, J.-K. Hao, and M. Sevaux, eds.: Fifth International Conference on Evolutionary Multi-Criterion Optimization (EMO 2009), LNCS 5467, pp. 155-168, Springer-Verlag, 2009

Tobias Glasmachers and Christian Igel. Second Order SMO Improves SVM Online and Active Learning. Neural Computation 20(2), pp. 374-382, 2008 source code

Christian Igel, Verena Heidrich-Meisner, and Tobias Glasmachers. Shark. Journal of Machine Learning Research 9, pp. 993-996, 2008 source code

Susanne Winter, Bernhard Brendel, Ioannis Pechlivanis, Kirsten Schmieder, and Christian Igel. Registration of CT and Intraoperative 3D Ultrasound Images of the Spine Using Evolutionary and Gradient-based Methods. IEEE Transactions on Evolutionary Computation, 12(3), pp. 284–296, 2008

Christian Igel and Bernhard Sendhoff. Genesis of Organic Computing Systems: Coupling Evolution and Learning. In R. Würtz, ed.: Organic Computing, Chapter 7, pp. 141-166, Springer-Verlag, 2008

Tobias Glasmachers and Christian Igel. Uncertainty Handling in Model Selection for Support Vector Machines. In G. Rudolph, ed.: Parallel Problem Solving from Nature (PPSN X), LNCS 5199, pp. 185-194, Springer-Verlag, 2008

Verena Heidrich-Meisner and Christian Igel. Learning Behavioral Policies using Extrinsic Perturbations on the Level of Synapses. Frontiers in Computational Neuroscience. Conference Abstract: Bernstein Symposium 2008, 2008, doi:10.3389/conf.neuro.10.2008.01.060

Verena Heidrich-Meisner and Christian Igel. Evolution Strategies for Direct Policy Search. In G. Rudolph, ed.: Parallel Problem Solving from Nature (PPSN X), LNCS 5199, pp. 428-437, Springer-Verlag, 2008

Verena Heidrich-Meisner and Christian Igel. Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem. In Girgin et al., eds.: European Workshop on Reinforcement Learning (EWRL 2008), LNAI 5323, pp. 136-150, Springer-Verlag, 2008

Verena Heidrich-Meisner and Christian Igel. Similarities and differences between policy gradient methods and evolution strategies. In M. Verleysen, ed.: 16th European Symposium on Artificial Neural Networks (ESANN 2008), pp. 149-154, Belgium: d-side publications, 2008

Verena Heidrich-Meisner and Christian Igel. Uncertainty Handling in Evolutionary Direct Policy Search. In Y. Engel, M. Ghavamzadeh, P. Poupart, and S. Mannor, eds.: NIPS-08 Workshop on Model Uncertainty and Risk in Reinforcement Learning, 2008

Thorsten Suttorp and Christian Igel. Approximation of Gaussian Process Regression Models after Training. In M. Verleysen, ed.: 16th European Symposium on Artificial Neural Networks (ESANN 2008), pp. 427-432, Belgium: d-side publications, 2008 source code

Thomas Voß, Nicola Beume, Günter Rudolph, Christian Igel. Scalarization versus Indicator-based Selection in Multi-objective CMA Evolution Strategies. Congress on Evolutionary Computation 2008 (CEC 2008), pp. 3041-3048, IEEE Press, 2008

Christian Igel, Nikolaus Hansen, and Stefan Roth. Covariance Matrix Adaptation for Multi-objective Optimization. Evolutionary Computation 15(1), pp. 1-28, 2007 source code

Christian Igel, Tobias Glasmachers, Britta Mersch, Nico Pfeifer, and Peter Meinicke. Gradient-based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection. IEEE/ACM Transactions on Computational Biology and Bioinformatics 4(2), pp. 216-226, 2007 source code & supplementary material

Britta Mersch, Tobias Glasmachers, Peter Meinicke, and Christian Igel. Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. International Journal of Neural Systems 17(5), selected paper of ICANN 2006, pp. 369-381, 2007 source code & supplementary material

Jens Niehaus, Christian Igel, and Wolfgang Banzhaf. Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database. Evolutionary Computation, 15(2), pp. 199-221, 2007

Verena Heidrich-Meisner, Martin Lauer, Christian Igel, and Martin Riedmiller. Reinforcement Learning in a Nutshell. In M. Verleysen, ed.: 15th European Symposium on Artificial Neural Networks (ESANN 2007), Belgium: d-side publications, pp. 277-288, 2007

Christian Igel, Thorsten Suttorp, and Nikolaus Hansen. Steady-state Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES. In S. Obayashi et al., eds.: Proceedings of the Fourth International Conference on Evolutionary Multi-Criterion Optimization (EMO 2007), LNCS 4403, pp. 171-185, Springer-Verlag, 2007 source code

Thorsten Suttorp and Christian Igel. Resilient Approximation of Kernel Classifiers. In J. Marques de Sá et al., eds.: International Conference on Artificial Neural Networks (ICANN 2007), LNCS 4668, pp. 139-148, Springer-Verlag, 2007 source code

Karin Liebenrodt, Martin H. J. Busch, Serban Mateiescu, Christian Igel, Susanne Winter, and Dietrich H. W. Grönemeyer. Protonenresonanzspektroskopie des Gehirns mit kurzer Echozeit: Unterstützung der Gewebeklassifizierung durch künstliche neuronale Netzwerke, Biomedizinische Technik (BMT), 52 (suppl.), 2007

Jan Salmen, Thorsten Suttorp, Johann Edelbrunner, and Christian Igel. Evolutionary Optimization of Wavelet Feature Sets for Real-Time Pedestrian Classification. In A. König, M. Köppen, A. Abraham, C. Igel, and N. Kasabov, eds.: International Conference on Hybrid Intelligent Systems (HIS 2007), pp. 222-227, IEEE Computer Society, 2007

Tobias Glasmachers and Christian Igel. Maximum-Gain Working Set Selection for SVMs. Journal of Machine Learning Research 7, pp. 1437-1466, 2006 source code and supplementary information

Thorsten Suttorp and Christian Igel. Multi-objective optimization of support vector machines. In Y. Jin, ed.: Multi-objective Machine Learning, pp. 199-220, Studies in Computational Intelligence, Springer-Verlag, 2006

Stefan Roth, Alexander Gepperth, and Christian Igel. Multi-objective neural network optimization for visual object detection. In Y. Jin, ed.: Multi-objective Machine Learning, pp. 629-655, Studies in Computational Intelligence, Springer-Verlag, 2006

Christian Igel, Thorsten Suttorp, and Nikolaus Hansen. A Computational Efficient Covariance Matrix Update and a (1+1)-CMA for Evolution Strategies. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2006), pp. 453-460, ACM Press, 2006 source code

Britta Mersch, Tobias Glasmachers, Peter Meinicke, and Christian Igel. Evolutionary Optimization of Sequence Kernels for Detection of Bacterial Gene Starts. In S. Kollias et al., eds.: International Conference on Artificial Neural Networks (ICANN 2006), LNCS 4132, pp. 827-836, Springer-Verlag, 2006 source code & supplementary material

Tobias Glasmachers and Christian Igel. Gradient-based Adaptation of General Gaussian Kernels. Neural Computation 17(10), pp. 2099-2105, 2005

Antonio Pellecchia, Christian Igel, Johann Edelbrunner, and Gregor Schöner. Making Driver Modeling Attractive. IEEE Intelligent Systems 20(2), pp. 8-12, 2005

Frauke Friedrichs and Christian Igel. Evolutionary Tuning of Multiple SVM Parameters. Neurocomputing 64(C), pp. 107-117, 2005

Christian Igel, Marc Toussaint, and Wan Weishui. Rprop Using the Natural Gradient. In M. G. de Bruin, D. H. Mache, and J. Szabados, eds.: Trends and Applications in Constructive Approximation. International Series of Numerical Mathematics, vol. 151, pp. 259-272, Birkhäuser Verlag, 2005

Christian Igel, Frauke Friedrichs, and Stefan Wiegand. Evolutionary Optimization of Neural Systems: The Use of Strategy Adaptation. In M. G. de Bruin, D. H. Mache, and J. Szabados, eds.: Trends and Applications in Constructive Approximation. International Series of Numerical Mathematics, vol. 151, pp. 103-123, Birkhäuser Verlag, 2005

Susanne Winter, Bernhard Brendel, and Christian Igel. Registration of bone structures in 3D ultrasound and CT data: Comparison of different optimization strategies. In H. U. Lemke, K. Inamura, K. Doi, M. W. Vannier, and A. G. Farman, eds.: Computer Assisted Radiology and Surgery (CARS 2005), International Congress Series 1281, pp. 242-247, Elsevier, 2005

Christian Igel and Bernhard Sendhoff. Synergies between Evolutionary and Neural Computation. In M. Verleysen, ed.: 13th European Symposium on Artificial Neural Networks (ESANN 2005), pp. 241-252, Belgium: d-side publications, 2005

Christian Igel. Multiobjective Model Selection for Support Vector Machines. In C. A. Coello Coello, E. Zitzler, and A. Hernandez Aguirre, eds.: Proceedings of the Third International Conference on Evolutionary Multi-Criterion Optimization (EMO 2005), LNCS 3410, pp. 534-546, Springer-Verlag, 2005

Susanne Winter, Bernhard Brendel, and Christian Igel. Registrierung von Knochen in 3D-Ultraschall- und CT-Daten: Vergleich verschiedener Optimierungsverfahren. In Bildverarbeitung für die Medizin (BVM), pp. 345-149, Springer-Verlag, 2005

Christian Igel and Karl-Heinz Temme. The Chaining Syllogism in Fuzzy Logic. IEEE Transactions on Fuzzy Systems 12(6), pp. 849-853, 2004 (extended version)

Stefan Wiegand, Christian Igel, and Uwe Handmann. Evolutionary Multi-Objective Optimization of Neural Networks for Face Detection. International Journal of Computational Intelligence and Applications, Special Issue on Neurocomputing and Hybrid Methods for Evolving Intelligence 4(3), pp. 237-253, 2004

Christian Igel and Marc Toussaint. A No-Free-Lunch Theorem for Non-Uniform Distributions of Target Functions. Journal of Mathematical Modelling and Algorithms 3(4), pp. 313-322, 2004

Stefan Schneider, Christian Igel, Christian Klaes, Hubert R. Dinse, and Jan C. Wiemer. Evolutionary adaptation of nonlinear dynamical systems in computational neuroscience. Genetic Programming and Evolvable Machines 5(2), Special Issue on Biological Applications of Genetic and Evolutionary Computation, pp. 215-227, 2004

Thomas Wiebringhaus, Christian Igel, and Jutta Gebert. Protein Fold Class Prediction Using Neural Networks with Tailored Early-Stopping. International Joint Conference on Neural Networks (IJCNN 2004), pp. 1693-1697, IEEE Press, 2004 note

Frauke Friedrichs and Christian Igel. Evolutionary Tuning of Multiple SVM Parameters. In M. Verleysen, ed.: 12th European Symposium on Artificial Neural Networks (ESANN 2004), pp. 519-524, Belgium: d-side publications, 2004 note

Stefan Wiegand, Christian Igel, and Uwe Handmann. Evolutionary Optimization of Neural Networks for Face Detection. In M. Verleysen, ed.: 12th European Symposium on Artificial Neural Networks (ESANN 2004), pp. 139-144 Belgium: d-side publications, 2004

Christian Igel and Martin Kreutz. Operator Adaptation in Evolutionary Computation and its Application to Structure Optimization of Neural Networks. Neurocomputing 55(1-2), pp. 347-361, 2003 (uncorrected proof)

Torsten Mayr, Christian Igel, Gregor Liebsch, Ingo Klimant, and Otto S. Wolfbeis. Cross-Reactive Metal Ion Sensor Array in a Microtiterplate Format. Analytical Chemistry 75(17), pp. 4389-4396, 2003

Christian Igel and Marc Toussaint. Neutrality and Self-Adaptation. Natural Computing 2(2), pp. 117-132, 2003

Christian Igel and Marc Toussaint. On Classes of Functions for which No Free Lunch Results Hold. Information Processing Letters 86(6), pp. 317-321, 2003

Thomas Bücher, Cristobal Curio, Johann Edelbrunner, Christian Igel, David Kastrup, Iris Leefken, Gesa Lorenz, Axel Steinhage, and Werner von Seelen. Image Processing and Behaviour Planning for Intelligent Vehicles. IEEE Transactions on Industrial Electronics 50(1), pp. 62-75, 2003

Christian Igel and Michael Hüsken. Empirical Evaluation of the Improved Rprop Learning Algorithm. Neurocomputing 50(C), pp. 105-123, 2003 source code

Christian Igel. Neuroevolution for Reinforcement Learning Using Evolution Strategies. In R. Sarker, R. Reynolds, H. Abbass, K. C. Tan, B. McKay, D. Essam, and T. Gedeon, eds.: Congress on Evolutionary Computation 2003 (CEC 2003), Volume 4, pp. 2588-2595, IEEE Press, 2003

Thomas Wiebringhaus, Ulrich Faigle, Dietmar Schomburg, Jutta Gebert, Christian Igel, and Gerhard-Wilhelm Weber. Protein Fold Class Prediction Using Neural Networks Reconsidered. Currents in Computational Molecular Biology, The Seventh Annual International Conference on Research in Computational Molecular Biology (RECOMB 2003), pp. 225-226, 2003

Michael Hüsken, Christian Igel, and Marc Toussaint. Task-Dependent Evolution of Modularity in Neural Networks. Connection Science 14(3), pp. 219-229, 2002

Christian Igel and Peter Stagge. Effects of Phenotypic Redundancy in Structure Optimization. IEEE Transactions on Evolutionary Computation 6(1), pp. 74-85, 2002

Christian Igel, Werner von Seelen, Wolfram Erlhagen, and Dirk Jancke. Evolving Field Models for Inhibition Effects in Early Vision. Neurocomputing 44-46(C), pp. 467-472, 2002

Hubert R. Dinse, Michael Hüsken, Christian Igel, Christian Klaes, Marc Nunkesser, Stefan Schneider, and Jan Wiemer. Derandomized Evolution Strategies in Computational Neuroscience. In A. Barry, ed.: 2002 Genetic and Evolutionary Computation Conference Workshop Program (GECCO 2002): Biological Applications of Genetic and Evolutionary Computation (BioGEC 2002), pp. 35-37, 2002

Michael Hüsken and Christian Igel. Balancing Learning and Evolution. In W. B. Langdon, E. Cantu-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M. A. Potter, A. C. Schultz, J. F. Miller, E. Burke, and N. Jonoska, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2002), pp. 391-398, 2002, Morgan Kaufmann, 2002

Christian Igel and Peter Stagge. Graph Isomorphisms Affect Structure Optimization of Neural Networks. International Joint Conference on Neural Networks 2002 (IJCNN 2002), pp. 142-147, IEEE Press, 2002

Marc Toussaint and Christian Igel. Neutrality: A Necessity for Self-Adaptation. Congress on Evolutionary Computation 2002 (CEC 2002), pp. 1354-1359, IEEE Press, 2002

Christian Igel, Wolfram Erlhagen, and Dirk Jancke. Optimization of Dynamic Neural Fields. Neurocomputing 36(1-4), pp. 225-233, 2001

Thomas Bergener, Carsten Bruckhoff and Christian Igel. Parameter Optimization for Visual Obstacle Detection Using a Derandomized Evolution Strategy. In J. Blanc-Talon and D. Popescu, eds.: Imaging and Vision Systems: Theory, Assessment and Application. Advances in Computation: Theory and Practice 9, Chapter 13, pp. 265-279, NOVA Science Books, 2001

Christian Igel and Martin Kreutz. Operator Adaptation in Structure Optimization of Neural Networks. In L. Spector, E. Goodman, A. Wu, W.B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. Garzon, and E. Burke, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '01), p. 1094, Morgan Kaufmann Publishers, 2001

Johann Edelbrunner, Uwe Handmann, Christian Igel, Iris Leefken and Werner von Seelen. Application and Optimization of Neural Field Dynamics for Driver Assistance. In The IEEE 4th International Conference on Intelligent Transportation Systems (ITSC '01), pp. 309-314, IEEE Press, 2001.

Peter Stagge and Christian Igel. Structure Optimization and Isomorphisms. In L. Kallel, B. Naudts and A. Rogers, eds.: Theoretical Aspects of Evolutionary Computing, Natural Computing series, pp. 409-422, Springer-Verlag, 2001

Peter Stagge and Christian Igel. Neural Network Structures and Isomorphisms: Random Walk Characteristics of the Search Space. In X. Yao and D. B. Fogel, eds.: 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks (ECNN), pp. 82-90, IEEE press, 2000

Christian Igel and Michael Hüsken. Improving the Rprop Learning Algorithm. In H. Bothe and R. Rojas, eds.: Second International Symposium on Neural Computation (NC 2000), pp. 115-121, ICSC Academic Press, 2000 source code

Thomas Bergener, Carsten Bruckhoff and Christian Igel. Evolutionary Parameter Optimization for Visual Obstacle Detection. In J. Blanc-Talon and D. Popescu, eds.: Advanced Concepts for Intelligent Vision Systems (ACIVS'99), pp. 104-109, The International Institute for Advanced Studies in Systems Research and Cybernetics, 1999

Christian Igel and Kumar Chellapilla. Fitness Distributions: Tools for Designing Efficient Evolutionary Computations. In L. Spector, W. B. Langdon, U.-M. O'Reilly, and P. J. Angeline, eds.: Advances in Genetic Programming 3, Chapter 9, pp. 191-216, MIT Press, 1999

Christian Igel and Kumar Chellapilla. Investigating the Influence of Depth and Degree of Genotypic Change on Fitness in Genetic Programming. In W. Banzhaf, J. Daida, A. E. Eiben, M. H. Garzon, V. Honavar, M. Jakiela and R. E. Smith, eds.: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO '99), Volume 2, pp. 1061-1068, Morgan Kaufmann Publishers, 1999 note

Christian Igel and Martin Kreutz. Using Fitness Distributions to Improve the Evolution of Learning Structures. Congress on Evolutionary Computation (CEC 99), Volume 3, pp. 1902-1909, IEEE Press, 1999

Christian Igel. Causality of Hierarchical Variable Length Representations. Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC'98), pp. 324-329, IEEE Press, 1998

Christian Igel and Karl-Heinz Temme. Chaining Syllogism Applied to Fuzzy If-Then Rules and Rule Bases. In B. Reusch, ed.: Computational Intelligence - Theory and Applications, LNCS 1226, pp. 179-188, Springer-Verlag, 1997

Christian Igel et al.: Proceedings of the Sixteenth International Conference on Genetic and Evolutionary Computation (GECCO 2014). ACM Press, 2014 (editor-in-chief)

Christian Blum et al.: Proceedings of the Ffteenth International Conference on Genetic and Evolutionary Computation (GECCO 2013), ACM Press, 2013 (ESEP track chair)

Terence Soule, Anne Auger, Christian Blum, Jürgen Branke, Nicolas Bredeche, Will Neil Browne, John Andrew Clark, Kalyanmoy Deb, Alan Dorin, Rene Doursat, Aniko Ekart, Tobias Friedrich, Steven Gustafson, Gregory S. Hornby, Christian Igel, Tim Kovacs, Dario Landa-Silva, Fernando G. Lobo, Gisele Lobo Pappa, Jose A. Lozano, Silja Meyer-Nieberg, Alison Motsinger, Frank Neumann, Gabriela Ochoa, Gustavo Olague, Yew-Soon Ong, Martin Pelikan, David Pelta, Clara Pizzuti, Mike Preuss, Jonathan Rowe, Stephen Leslie Smith, Christine Solnon, Giovanni Squillero, Daniel Tauritz, Man Leung Wong, Shin Yoo, and Tina Yu, eds.: Proceedings of the Fourteenth International Conference on Genetic and Evolutionary Computation (GECCO 2012), ACM Press, 2012 (ESEP track chair)

Andreas König, Mario Köppen, Ajith Abraham, Christian Igel, and Nikola Kasabov, eds.: International Conference on Hybrid Intelligent Systems (HIS 2007), IEEE Computer Society, 2007

Christian Igel. Optimization of Support Vector Machines, Habiltation thesis, Faculty of Electrical Engineering and Information Technology, Ruhr-Universität Bochum, 2010

Christian Igel. Beiträge zum Entwurf neuronaler Systeme, Doctoral thesis, University of Bielefeld, Faculty of Technology, Shaker-Verlag, Aachen, Germany, ISBN: 3-8322-1103-9

Christian Igel. Untersuchungen zur Kettenregel für Fuzzy-Regeln und Regelbasen mit implikationsbasierter Semantik, Diploma thesis, University of Dortmund, Department of Computer Science, 1997

Bobby Z. S. Lo, Bjørn Møller, Christian Igel, Signe Wildt, Ida Vind, Flemming Bendtsen, Johan Burisch, and Bulat Ibragimov. Validating and enhancing real-time disease severity classification in ulcerative colitis: Artificial intelligence as a second opinion trigger. Journal of Crohn’s and Colitis 18:i1163–i1164, 2024.

Erik B. Dam, Arjun Desai, Cem M. Deniz, H. Rajamohan, Ravinder Regatte, Claudia Iriondo, Valentina Pedoia, Sharmila Majumdar, Mathias Perslev, Christian Igel, Akshay Pai, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Hasan Maqbool, Ismail Irmakci, Sang-Eun Song, Ulas Bagci, Brian A. Hargreaves, Garry E. Gold, and Akshay S. Chaudhari. Multi-institutional large-scale validation of 8 methods for automatic knee MRI segmentation for use in clinical trials. Osteoarthritis and Cartilage 30:S291–S292, 2022

Mathias Perslev, Anders Sode West, Sofie Amalie Simonsen, Laura Bødker Ponsaing, Helle Klingenberg Iversen, Christian Igel, Poul Jørgen Jennum. Automatic detection of abnormal sleeping patterns in stroke patients using high-frequency sleep staging. Journal of Sleep Research 31, 2022

Bobby Lo, ZhuoYuan Liu, Flemming Bendtsen, Christian Igel, Ida Vind, and Johan Burisch. Artificial intelligence surpasses gastrointestinal experts in the classification of endoscopic severity among Ulcerative Colitis. Journal of Crohn's & Colitis 15 Suppl 1, p. S007, 2021

Jaime Caballer Revenga, Katerina Trepekli, Stefan Oehmcke, Fabian Gieseke, Christian Igel, Rasmus Jensen, and Thomas Friborg. Prediction of above ground biomass and C-stocks based on UAV-LiDAR, multispectral imagery and machine learning methods. EGU General Assembly, 2021

Arjun D. Desai, Francesco Caliva, Claudia Iriondo, Naji Khosravan, Aliasghar Mortazi, Sachin Jambawalikar, Drew Torigian, Jutta Ellerman, Mehmet Akcakaya, Ulas Bagci, Radhika Tibrewala, Io Flament, Matthew O'Brien, Sharmila Majumdar, Mathias Perslev, Akshay Pai, Christian Igel, Erik B. Dam, Sibaji Gaj, Mingrui Yang, Kunio Nakamura, Xiaojuan Li, Cem M. Deniz, Vladimir Juras, Ravinder Regatte, Garry E. Gold, Brian A. Hargreaves, Valentina Pedoia, and Akshay S. Chaudhari. A multi-institute automated segmentation evaluation on a standard dataset: Findings from the international workshop on osteoarthritis imaging segmentation challenge. Osteoarthritis and Cartilage 28, pp. S304–S305, 2020

Mathias Perslev, Akshay Pai, Christian Igel, Jos Runhaar, and Erik Dam. Validation of an open source, generic deep learning architecture for 3D MRI segmentation - with data from the OAI, PROOF, and CCBR. Osteoarthritis and Cartilage 27(Supplement 1), pp. S393–S394, 2019

Mathias Perslev, Akshay Pai, Christian Igel, and Erik Dam. Knee Segmentation by Multiplanar Deep Learning Network - with data from OAI. International Workshop on Osteoarthritis Imaging, 2018

Lauge Sørensen, Christian Igel, and Mads Nielsen. MCI trial enrichment using MRI hippocampus texture. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association, 2016

Michiel Kallenberg, Martin Lilholm, Pengfei Diao, Katharina Holland, Nico Karssemeijer, Christian Igel, and Mads Nielsen. Assessing breast cancer masking risk in full field digital mammography with automated texture analysis. In 7th International Workshop on Breast Densitometry and Cancer Risk Assessment (Non-CME), p. 109. University of California, 2015

Michiel Kallenberg, Martin Lilholm, Pengfei Diao, Kersten Petersen, Katharina Holland, Nico Karssemeijer, Christian Igel, and Mads Nielsen. Assessing breast cancer masking risk with automated texture analysis in full field digital mammography. In Breast Imaging and Interventional, p. 218. Radiological Society of North America, Inc, 2015

Michiel Kallenberg, Kersten Petersen, Martin Lilholm, Dan Richter Jørgensen, Pengfei Diao, Katharina Holland, Nico Karssemeijer, Christian Igel, and Mads Nielsen. Automated texture scoring for assessing breast cancer masking risk in full field digital mammography. In European Congress of Radiology (ERC 2015), 2015

Jan Kremer, Kim Steenstrup Pedersen, and Christian Igel. Support vector machines for active learning. In E uropean Conference on Data Analysis (ECDA), 2014

Lauge Sørensen, Akshay Pai, Christian Igel, and Mads Nielsen. Hippocampal MRI texture is related to hippocampal glucose metabolism. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association 11(7, Supplement):P55–P56, 2015

Mads Nielsen, Christian Igel, and Lauge Sørensen. Hippocampal texture predicts ad conversion in amyloid positive mild cognitively impaired subjects. Neurodegenerative Diseases 15(Suppl. 1):262, 2015

Lauge Sørensen, Martin Lillholm, Akshay Pai, Ioana Balas, Cecilie Anker, Christian Igel, and Mads Nielsen. Improved alzheimer’s disease diagnostic performance using structural MRI: validation of the MRI combination biomarker that won the caddementia challenge. In ECR 2015 Book of Abstracts - B - Scientific Sessions and Late-Breaking Clinical Trials, p. S177. Springer-Verlag, 2015

Mads Nielsen, Lauge Sørensen, Akshay Pai, Christian Igel, and Martin Lillholm. Hippocampus MRI T1 texture’s relation to established alzheimer’s disease biomarkers and prediction of progression. In 101st Scientific Assembly and Annual Meeting of the Radiological Society of North America, 2015

Lauge Sørensen, Christian Igel, Naja Liv Hansen, Martin Lauritzen, Merete Osler, Egil Rostrup, and Mads Nielsen. Validation of hippocampal texture for early Alzheimers disease detection: Generalization to independent cohorts and extrapolation to very early signs of dementia. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association 10(4, AAIC supplement):P139, 2014

Lauge Sørensen, Christian Igel, Naja Liv Hansen, Martin Lauritzen, Merete Osler, Egil Rostrup, and Mads Nielsen. Validation of hippocampal texture for early Alzheimers disease detection: Generalization to independent cohorts and extrapolation to very early signs of dementia. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association 10(4, AIC supplement):P133, 2014

Matthias Tuma, Christian Igel, and P. Mialle. Kernel-based machine learning techniques for infrasound signal classification. European Geosciences Union General Assembly 2014, 2014

Matthias Tuma and Christian Igel. Investigation of Kernel-Based Machine Learning Techniques for Infrasound Signal Classification. CTBTO Science and Technology (SNT 2013), T3-P67 , 2013

Matthias Tuma, Christian Igel, and Mark Prior. Joint Optimization of a Signal Processing Chain for Hydroacoustic Signal Classification. CTBTO Science and Technology (SNT 2013), T3-P69, 2013

Lauge Sørensen, Akshay Pai, Sune Darkner, Gennan Chen, Joonmi Oh, Joyce Suhy, Christian Igel, and Mads Nielsen. Hippocampal Texture Predicts One-Year Hippocampal Atrophy in Mild Cognitively Impaired Subjects. European Congress on Radiology, 2013

Lauge Sørensen, Akshay Pai and Christian Igel and Mads Nielsen. Hippocampal Texture Predicts Conversion from MCI to AD. Alzheimer's Association International Conference, Alzheimer's and Dementia 9(4), suppl., P581, 2013

Lauge Sørensen, Akshay Pai and Christian Igel and Mads Nielsen. Hippocampal Texture Predicts Conversion from MCI to AD. Alzheimer's Imaging Consortium, Alzheimer's and Dementia 9(4), suppl., P52 2013

Lauge Sørensen, Akshay Pai, Sune Darkner, Joyce Suhy, Joommi Oh, Gennan Chen, Christian Igel, Mads Nielsen. Hippocampal Texture Provides Volume Independent Information for Alzheimer’s Disease Diagnosis. Alzheimer's & Dementia: The Journal of the Alzheimer’s Association 8(4) supplement, P162–P163, 2012

Lauge Sørensen, Akshay Pai, Sune Darkner, Joyce Suhy, Joommi Oh, Gennan Chen, Christian Igel, Mads Nielsen. Hippocampal Texture Provides Volume Independent Information for Alzheimer’s Diagnosis. Alzheimer's & Dementia: The Journal of the Alzheimer’s Association 8(4), supplement, P15, IC-P-013, 2012

Asja Fischer and Christian Igel. Bounding the Bias of Contrastive Divergence Used for Maximum Likelihood Learning in Restricted Boltzmann Machines. In: Second Joint Statistical Meeting Deutsche Arbeitsgemeinschaft Statistik `Statistics under one umbrella' (DAGStat 2010), p. 98, 2010

Matthias Tuma and Christian Igel. Automatic Classification of Hydroacoustic Signals to Support Verification of the Comprehensive Nuclear-Test-Ban Treaty. In: Second Joint Statistical Meeting Deutsche Arbeitsgemeinschaft Statistik `Statistics under one umbrella' (DAGStat 2010), p. 361, 2010

Valentin Markounikau, Christian Igel, and Dirk Jancke. Neural Field Models of Early Cortical Processing of Real and Apparent Motion. In: Computational Vision and Neuroscience Symposium, p. 36. Max Planck Institute for Biological Cybernetics, Tübingen, 2008

Christian Igel. Efficient Covariance Matrix Update for Evolution Strategies. In D. V. Arnold, A. Auger, J. E. Rowe, and C. Witt, eds.: Theory of Evolutionary Algorithms, Dagstuhl Seminar Proceedings 08051, Abstract Collection. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, 2008

Jennifer Meyer, Dirk Jancke, and Christian Igel. Modelling cortical activity underlying apparent and real motion perception. In K.-A. Hossmann, ed.: Symposium `Neuro-Visionen 4, Perspektiven in Nordrhein-Westfalen', pp. 257-258. Verlag Ferdinand Schöningh, 2007

Christian Igel. Computational Efficient Covariance Matrix Update and the Multi-objective Variable Metric Evolution Strategy. In D. V. Arnold, T. Jansen, J. E. Rowe, and M. D. Vose, eds.: Theory of Evolutionary Algorithms, Dagstuhl Seminar Proceedings 06061, Abstract Collection. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, 2006

Christian Igel. The Bias-Invariance Dilemma. In K. Bellman, P. Hofmann, C. Müller-Schloer, H. Schmeck, and R.Würtz, eds.: Organic Computing - Controlled Emergence, Dagstuhl Seminar Proceedings 06031, Abstract Collection. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, 2006

Jennifer Meyer, Christian Igel, and Dirk Jancke. Modelling dynamic activity patterns in early visual cortex based on voltage sensitive dye experiments. In K.-A. Hossmann, ed.: Symposium `Neuro-Visionen 3, Perspektiven in Nordrhein-Westfalen', pp. 193-195. Verlag Ferdinand Schöningh, 2006

Christian Igel: Recent Results on No-Free-Lunch for Optimization. In H.-G. Beyer, T. Jansen, C. Reeves, and M. D. Vose, eds.: Theory of Evolutionary Algorithms, Dagstuhl Seminar Proceedings 04081, Abstract Collection. Internationales Begegnungs- und Forschungszentrum für Informatik (IBFI), Schloss Dagstuhl, 2004.

Christian Igel and Werner von Seelen. Design of a Field Model for Early Vision: A Case Study of Evolutionary Algorithms in Neuroscience. In N. Elsner and G. W. Kreutzberg, eds.: Göttingen Neurobiology Report 2001, Volume 2, p. 1034, Georg Thieme Verlag, 2001

Michael Hüsken, Christian Igel, and Marc Toussaint. Task-Dependent Evolution of Modularity in Neural Networks - A Quantitative Case Study. In Erik D. Goodman, ed.: Late Breaking Papers at the 2001 Genetic and Evolutionary Computation Conference, pp. 187-193, 2001

Jens Busse, Hans-Jürgen Röhm, Sascha Wenzel, Gerd Emmrich, and Christian Igel. Zur Auslegung von thermisch und stofflich gekoppelten Destillationskolonnen mit evulutionären Algorithmen, GVC / DECHEMA Fachausschuss Prozess- und Anlagentechnik, 2001

Ürün Dogan, Tobias Glasmachers, and Christian Igel. Fast Training of Multi-class Support Vector Machines. Technical Report no. 03/2011, Department of Computer Science, Faculty of Science, University of Copenhagen, 2011

Christian Igel, Nikolaus Hansen, and Stefan Roth. The Multi-objective Variable Metric Evolution Strategy, Part I. Technical Report, IRINI-2001-04, Institut für Neuroinformatik, 2005

Tobias Glasmachers and Christian Igel. Maximum-Gain Working Set Selection for Support Vector Machines. Technical Report, IRINI-2005-03, Institut für Neuroinformatik, 2005 source code and supplementary information

Jens Niehaus, Christian Igel, and Wolfgang Banzhaf. Graph Genetic Programming and Neutrality. Technical Report, IRINI-2005-02, Institut für Neuroinformatik, 2005

Britta Mersch, Nico Pfeifer, Tobias Glasmachers, Peter Meinicke, and Christian Igel. Gradient-based Optimization of Kernel-Target Alignment for Sequence Kernels Technical Report, IRINI-2005-01, Institut für Neuroinformatik, 2005

Christian Igel and Martin Kreutz. Operator Adaptation in Evolutionary Computation and its Application to Structure Optimization of Neural Networks. Technical Report, IRINI-2001-03, Institut für Neuroinformatik, 2001