Chaining Syllogism Applied to Fuzzy IF-THEN Rules and Rule Bases. - Christian Igel; Karl-Heinz Temme (Fuzzy Days, 1997)

Using fitness distributions to improve the evolution of learning structures. - Christian Igel; Martin Kreutz (CEC, 1999)

Optimization of dynamic neural fields. - Christian Igel; Wolfram Erlhagen; Dirk Jancke (Neurocomputing, 2001)

Neutrality: a necessity for self-adaptation. - Marc Toussaint; Christian Igel (IEEE Congress on Evolutionary Computation, 2002)

Balancing Learning And Evolution. - Michael Hüsken; Christian Igel (GECCO, 2002)

Evolving field models for inhibition effects in early vision. - Christian Igel; Werner von Seelen; Wolfram Erlhagen; Dirk Jancke (Neurocomputing, 2002)

Effects of phenotypic redundancy in structure optimization. - Christian Igel; Peter Stagge (IEEE Trans. Evol. Comput., 2002)

Neuroevolution for reinforcement learning using evolution strategies. - Christian Igel (IEEE Congress on Evolutionary Computation, 2003)

Recent Results on No-Free-Lunch Theorems for Optimization - Christian Igel; Marc Toussaint (CoRR, 2003)

Empirical evaluation of the improved Rprop learning algorithms. - Christian Igel; Michael Hüsken (Neurocomputing, 2003)

Operator adaptation in evolutionary computation and its application to structure optimization of neural networks. - Christian Igel; Martin Kreutz (Neurocomputing, 2003)

On classes of functions for which No Free Lunch results hold. - Christian Igel; Marc Toussaint (Inf. Process. Lett., 2003)

Neutrality and self-adaptation. - Christian Igel; Marc Toussaint (Nat. Comput., 2003)

Image processing and behavior planning for intelligent vehicles. - Thomas Bücher; Cristóbal Curio; Johann Edelbrunner; Christian Igel; David Kastrup; Iris Leefken; Gesa Lorenz; Axel Steinhage; Werner von Seelen (IEEE Trans. Ind. Electron., 2003)

Beiträge zum Entwurf neuronaler Systeme. - Christian Igel (Shaker, 2003)

Evolutionary Optimization of Neural Networks for Face Detection. - Stefan Wiegand; Christian Igel; Uwe Handmann (ESANN, 2004)

Protein fold class prediction using neural networks with tailored early-stopping. - Christian Igel; Jutta Gebert; Thomas Wiebringhaus (IJCNN, 2004)

Evolutionary Adaptation of Nonlinear Dynamical Systems in Computational Neuroscience. - Stefan Schneider 005; Christian Igel; Christian Klaes 001; Hubert R. Dinse; Jan C. Wiemer (Genet. Program. Evolvable Mach., 2004)

Evolutionary Multi-Objective Optimisation Of Neural Networks For Face Detection. - Stefan Wiegand; Christian Igel; Uwe Handmann (Int. J. Comput. Intell. Appl., 2004)

A No-Free-Lunch theorem for non-uniform distributions of target functions. - Christian Igel; Marc Toussaint (J. Math. Model. Algorithms, 2004)

The chaining syllogism in fuzzy logic. - Christian Igel; Karl-Heinz Temme (IEEE Trans. Fuzzy Syst., 2004)

Registrierung von Knochen in 3D-Ultraschall- und CT-Daten: Vergleich verschiedener Optimierungsverfahren. - Susanne Winter; Bernhard Brendel; Christian Igel (Bildverarbeitung für die Medizin, 2005)

Multi-objective Model Selection for Support Vector Machines. - Christian Igel (EMO, 2005)

Synergies between Evolutionary and Neural Computation. - Christian Igel; Bernhard Sendhoff (ESANN, 2005)

Making Driver Modeling Attractive. - Antonio Pellecchia; Christian Igel; Johann Edelbrunner; Gregor Schöner (IEEE Intell. Syst., 2005)

Evolutionary tuning of multiple SVM parameters. - Frauke Friedrichs; Christian Igel (Neurocomputing, 2005)

Gradient-Based Adaptation of General Gaussian Kernels. - Tobias Glasmachers; Christian Igel (Neural Comput., 2005)

A computational efficient covariance matrix update and a (1+1)-CMA for evolution strategies. - Christian Igel; Thorsten Suttorp; Nikolaus Hansen (GECCO, 2006)

Maximum-Gain Working Set Selection for SVMs. - Tobias Glasmachers; Christian Igel (J. Mach. Learn. Res., 2006)

Multi-Objective Neural Network Optimization for Visual Object Detection. - Stefan Roth 003; Alexander Rainer Tassilo Gepperth; Christian Igel (Multi-Objective Machine Learning, 2006)

Multi-Objective Optimization of Support Vector Machines. - Thorsten Suttorp; Christian Igel (Multi-Objective Machine Learning, 2006)

Steady-State Selection and Efficient Covariance Matrix Update in the Multi-objective CMA-ES. - Christian Igel; Thorsten Suttorp; Nikolaus Hansen (EMO, 2007)

Reinforcement learning in a nutshell. - Verena Heidrich-Meisner; Martin Lauer; Christian Igel; Martin A. Riedmiller (ESANN, 2007)

Evolutionary Optimization ofWavelet Feature Sets for Real-Time Pedestrian Classification. - Jan Salmen; Thorsten Suttorp; Johann Edelbrunner; Christian Igel (HIS, 2007)

Resilient Approximation of Kernel Classifiers. - Thorsten Suttorp; Christian Igel (ICANN (1), 2007)

Covariance Matrix Adaptation for Multi-objective Optimization. - Christian Igel; Nikolaus Hansen; Stefan Roth 003 (Evol. Comput., 2007)

Reducing the Number of Fitness Evaluations in Graph Genetic Programming Using a Canonical Graph Indexed Database. - Jens Niehaus; Christian Igel; Wolfgang Banzhaf (Evol. Comput., 2007)

Evolutionary Optimization of Sequence Kernels for Detection of bacterial gene Starts. - Britta Mersch; Tobias Glasmachers; Peter Meinicke; Christian Igel (Int. J. Neural Syst., 2007)

Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection. - Christian Igel; Tobias Glasmachers; Britta Mersch; Nico Pfeifer; Peter Meinicke (IEEE ACM Trans. Comput. Biol. Bioinform., 2007)

Genesis of Organic Computing Systems: Coupling Evolution and Learning. - Christian Igel; Bernhard Sendhoff (Organic Computing, 2008)

Scalarization versus indicator-based selection in multi-objective CMA evolution strategies. - Thomas Voß; Nicola Beume; Günter Rudolph; Christian Igel (IEEE Congress on Evolutionary Computation, 2008)

Similarities and differences between policy gradient methods and evolution strategies. - Verena Heidrich-Meisner; Christian Igel (ESANN, 2008)

Approximation of Gaussian process regression models after training. - Thorsten Suttorp; Christian Igel (ESANN, 2008)

Variable Metric Reinforcement Learning Methods Applied to the Noisy Mountain Car Problem. - Verena Heidrich-Meisner; Christian Igel (EWRL, 2008)

Uncertainty Handling in Model Selection for Support Vector Machines. - Tobias Glasmachers; Christian Igel (PPSN, 2008)

Evolution Strategies for Direct Policy Search. - Verena Heidrich-Meisner; Christian Igel (PPSN, 2008)

Shark. - Christian Igel; Verena Heidrich-Meisner; Tobias Glasmachers (J. Mach. Learn. Res., 2008)

Second-Order SMO Improves SVM Online and Active Learning. - Tobias Glasmachers; Christian Igel (Neural Comput., 2008)

Registration of CT and Intraoperative 3-D Ultrasound Images of the Spine Using Evolutionary and Gradient-Based Methods. - Susanne Winter; Bernhard Brendel; Ioannis Pechlivanis; Kirsten Schmieder; Christian Igel (IEEE Trans. Evol. Comput., 2008)

Recombination for Learning Strategy Parameters in the MO-CMA-ES. - Thomas Voß; Nikolaus Hansen; Christian Igel (EMO, 2009)

Uncertainty handling CMA-ES for reinforcement learning. - Verena Heidrich-Meisner; Christian Igel (GECCO, 2009)

Hoeffding and Bernstein races for selecting policies in evolutionary direct policy search. - Verena Heidrich-Meisner; Christian Igel (ICML, 2009)

Neuroevolution strategies for episodic reinforcement learning. - Verena Heidrich-Meisner; Christian Igel (J. Algorithms, 2009)

Gasteditorial Reinforcement Learning. - Christian Igel (Künstliche Intell., 2009)

Ontogenetic and Phylogenetic Reinforcement Learning. - Tom Schaul; Daan Wierstra; Faustino J. Gomez; Jürgen Schmidhuber; Christian Igel; Julian Togelius (Künstliche Intell., 2009)

Efficient covariance matrix update for variable metric evolution strategies. - Thorsten Suttorp; Nikolaus Hansen; Christian Igel (Mach. Learn., 2009)

Scaling up indicator-based MOEAs by approximating the least hypervolume contributor: a preliminary study. - Thomas Voß; Tobias Friedrich 001; Karl Bringmann; Christian Igel (GECCO (Companion), 2010)

Improved step size adaptation for the MO-CMA-ES. - Thomas Voß; Nikolaus Hansen; Christian Igel (GECCO, 2010)

Empirical Analysis of the Divergence of Gibbs Sampling Based Learning Algorithms for Restricted Boltzmann Machines. - Asja Fischer; Christian Igel (ICANN (3), 2010)

Hydroacoustic Signal Classification Using Kernel Functions for Variable Feature Sets. - Matthias Tuma; Christian Igel; Mark Prior (ICPR, 2010)

New Uncertainty Handling Strategies in Multi-objective Evolutionary Optimization. - Thomas Voß; Heike Trautmann; Christian Igel (PPSN (2), 2010)

Structure optimization of reservoir networks. - Benjamin Roeschies; Christian Igel (Log. J. IGPL, 2010)

Maximum Likelihood Model Selection for 1-Norm Soft Margin SVMs with Multiple Parameters. - Tobias Glasmachers; Christian Igel (IEEE Trans. Pattern Anal. Mach. Intell., 2010)

A Dynamic Neural Field Model of Mesoscopic Cortical Activity Captured with Voltage-Sensitive Dye Imaging. - Valentin Markounikau; Christian Igel; Amiram Grinvald; Dirk Jancke (PLoS Comput. Biol., 2010)

Efficient update of the covariance matrix inverse in iterated linear discriminant analysis. - Jan Salmen; Marc Schlipsing; Christian Igel (Pattern Recognit. Lett., 2010)

Editorial: Special issue on organic computing. - Rolf P. Würtz; Kirstie L. Bellman; Hartmut Schmeck; Christian Igel (ACM Trans. Auton. Adapt. Syst., 2010)

Evolutionary Kernel Learning. - Christian Igel (Encyclopedia of Machine Learning, 2010)

Towards exaggerated image stereotypes. - Chen Chen; François Lauze; Christian Igel; Aasa Feragen; Marco Loog; Mads Nielsen (ACPR, 2011)

Improved Working Set Selection for LaRank. - Matthias Tuma; Christian Igel (CAIP (1), 2011)

Real-Time Estimation of Optical Flow Based on Optimized Haar Wavelet Features. - Jan Salmen; Lukas Caup; Christian Igel (EMO, 2011)

Training RBMs based on the signs of the CD approximation of the log-likelihood derivatives. - Asja Fischer; Christian Igel (ESANN, 2011)

Non-linearly increasing resampling in racing algorithms. - Verena Heidrich-Meisner; Christian Igel (ESANN, 2011)

The logarithmic hypervolume indicator. - Tobias Friedrich 001; Karl Bringmann; Thomas Voß; Christian Igel (FOGA, 2011)

The German Traffic Sign Recognition Benchmark: A multi-class classification competition. - Johannes Stallkamp; Marc Schlipsing; Jan Salmen; Christian Igel (IJCNN, 2011)

Bounding the Bias of Contrastive Divergence Learning. - Asja Fischer; Christian Igel (Neural Comput., 2011)

Huge Music Archives on Mobile Devices. - Holger Blume; Bernd Bischl; Martin Botteck; Christian Igel; Rainer Martin 001; Günther Rötter; Günter Rudolph; Wolfgang M. Theimer; Igor Vatolkin; Claus Weihs (IEEE Signal Process. Mag., 2011)

An Introduction to Restricted Boltzmann Machines. - Asja Fischer; Christian Igel (CIARP, 2012)

Towards exaggerated emphysema stereotypes. - C. Chen; Lauge Sørensen; François Lauze; Christian Igel; Marco Loog; Aasa Feragen; Marleen de Bruijne; Mads Nielsen (Computer-Aided Diagnosis, 2012)

Cascaded classifier for large-scale data applied to automatic segmentation of articular cartilage. - Adhish Prasoon; Christian Igel; Marco Loog; François Lauze; Erik Dam; Mads Nielsen (Image Processing, 2012)

A Note on Extending Generalization Bounds for Binary Large-Margin Classifiers to Multiple Classes. - Ürün Dogan; Tobias Glasmachers; Christian Igel (ECML/PKDD (1), 2012)

Evolutionary kernel machines. - Oliver Kramer 001; Christian Igel; Günter Rudolph (Evol. Intell., 2012)

Learning ∈ Artificial Intelligence ∩ Cognitive Technologies ∩ Neural Computation ∩ ... - Christian Igel (Künstliche Intell., 2012)

Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition. - Johannes Stallkamp; Marc Schlipsing; Jan Salmen; Christian Igel (Neural Networks, 2012)

Introduction to the Special Issue on Machine Learning for Traffic Sign Recognition. - Johannes Stallkamp; Marc Schlipsing; Jan Salmen; Christian Igel (IEEE Trans. Intell. Transp. Syst., 2012)

Polynomial Runtime Bounds for Fixed-Rank Unsupervised Least-Squares Classification. - Fabian Gieseke; Tapio Pahikkala; Christian Igel (ACML, 2013)

Nearest neighbor classification using bottom-k sketches. - Søren Dahlgaard; Christian Igel; Mikkel Thorup (IEEE BigData, 2013)

Nearest neighbour regression outperforms model-based prediction of specific star formation rate. - Kristoffer Stensbo-Smidt; Christian Igel; Andrew Zirm; Kim Steenstrup Pedersen (IEEE BigData, 2013)

Femoral cartilage segmentation in Knee MRI scans using two stage voxel classification. - Adhish Prasoon; Christian Igel; Marco Loog; François Lauze; Erik B. Dam; Mads Nielsen (EMBC, 2013)

Shape Index Descriptors Applied to Texture-Based Galaxy Analysis. - Kim Steenstrup Pedersen; Kristoffer Stensbo-Smidt; Andrew Zirm; Christian Igel (ICCV, 2013)

Approximation properties of DBNs with binary hidden units and real-valued visible units. - Oswin Krause; Asja Fischer; Tobias Glasmachers; Christian Igel (ICML (1), 2013)

Detection of traffic signs in real-world images: The German traffic sign detection benchmark. - Sebastian Houben; Johannes Stallkamp; Jan Salmen; Marc Schlipsing; Christian Igel (IJCNN, 2013)

Deep Feature Learning for Knee Cartilage Segmentation Using a Triplanar Convolutional Neural Network. - Adhish Prasoon; Kersten Petersen; Christian Igel; François Lauze; Erik Dam; Mads Nielsen (MICCAI (2), 2013)

Speeding up many-objective optimization by Monte Carlo approximations. - Karl Bringmann; Tobias Friedrich 001; Christian Igel; Thomas Voß (Artif. Intell., 2013)

Echtzeit-Videoanalyse im Fußball - Ein Live-System zum Spieler-Tracking. - Marc Schlipsing; Jan Salmen; Christian Igel (Künstliche Intell., 2013)

The flip-the-state transition operator for restricted Boltzmann machines. - Kai Brügge 001; Asja Fischer; Christian Igel (Mach. Learn., 2013)

Linear feature selection in texture analysis - A PLS based method. - Joselene Marques; Christian Igel; Martin Lillholm; Erik B. Dam (Mach. Vis. Appl., 2013)

A Note on Generalization Loss When Evolving Adaptive Pattern Recognition Systems. - Christian Igel (IEEE Trans. Evol. Comput., 2013)

Speedy greedy feature selection: Better redshift estimation via massive parallelism. - Fabian Gieseke; Kai Lars Polsterer; Cosmin Eugen Oancea; Christian Igel (ESANN, 2014)

Buffer k-d Trees: Processing Massive Nearest Neighbor Queries on GPUs. - Fabian Gieseke; Justin Heinermann; Cosmin E. Oancea; Christian Igel (ICML, 2014)

Automatic FDG-PET-based tumor and metastatic lymph node segmentation in cervical cancer. - Dídac R. Arbonès; Henrik G. Jensen; Annika Loft; Per Munck af Rosenschöld; Anders E. Hansen; Christian Igel; Sune Darkner (Image Processing, 2014)

Training restricted Boltzmann machines: An introduction. - Asja Fischer; Christian Igel (Pattern Recognit., 2014)

Active learning with support vector machines. - Jan Kremer; Kim Steenstrup Pedersen; Christian Igel (WIREs Data Mining Knowl. Discov., 2014)

No Free Lunch Theorems: Limitations and Perspectives of Metaheuristics. - Christian Igel (Theory and Principled Methods for the Design of Metaheuristics, 2014)

Computational Complexity of Linear Large Margin Classification With Ramp Loss. - Søren Frejstrup Maibing; Christian Igel (AISTATS, 2015)

High-School Dropout Prediction Using Machine Learning: A Danish Large-scale Study. - Nicolae-Bogdan Sara; Rasmus Halland; Christian Igel; Stephen Alstrup (ESANN, 2015)

A More Efficient Rank-one Covariance Matrix Update for Evolution Strategies. - Oswin Krause; Christian Igel (FOGA, 2015)

Nearest neighbor density ratio estimation for large-scale applications in astronomy. - Jan Kremer; Fabian Gieseke; Kim Steenstrup Pedersen; Christian Igel (Astron. Comput., 2015)

Theory of Evolutionary Algorithms (Dagstuhl Seminar 15211). - Benjamin Doerr; Nikolaus Hansen; Christian Igel; Lothar Thiele (Dagstuhl Reports, 2015)

A bound for the convergence rate of parallel tempering for sampling restricted Boltzmann machines. - Asja Fischer; Christian Igel (Theor. Comput. Sci., 2015)

Parallelized rotation and flipping INvariant Kohonen maps (PINK) on GPUs. - Kai Lars Polsterer; Fabian Gieseke; Christian Igel; Bernd Doser; Nikolaos Gianniotis (ESANN, 2016)

Unbounded Population MO-CMA-ES for the Bi-Objective BBOB Test Suite. - Oswin Krause; Tobias Glasmachers; Nikolaus Hansen; Christian Igel (GECCO (Companion), 2016)

Learning Density Independent Texture Features. - Michiel Kallenberg; Mads Nielsen; Katharina Holland; Nico Karssemeijer; Christian Igel; Martin Lillholm (Digital Mammography / IWDM, 2016)

CMA-ES with Optimal Covariance Update and Storage Complexity. - Oswin Krause; Dídac Rodríguez Arbonès; Christian Igel (NIPS, 2016)

PAC-Bayesian Aggregation without Cross-Validation. - Niklas Thiemann; Christian Igel; Yevgeny Seldin (CoRR, 2016)

A Unified View on Multi-class Support Vector Classification. - Ürün Dogan; Tobias Glasmachers; Christian Igel (J. Mach. Learn. Res., 2016)

Separating Timing, Movement Conditions and Individual Differences in the Analysis of Human Movement. - Lars Lau Rakêt; Britta Grimme; Gregor Schöner; Christian Igel; Bo Markussen (PLoS Comput. Biol., 2016)

Integrated Optimization of Long-Range Underwater Signal Detection, Feature Extraction, and Classification for Nuclear Treaty Monitoring. - Matthias Tuma; Valdemar Rorbech; Mark Prior; Christian Igel (IEEE Trans. Geosci. Remote. Sens., 2016)

Unsupervised Deep Learning Applied to Breast Density Segmentation and Mammographic Risk Scoring. - Michiel Kallenberg; Kersten Petersen; Mads Nielsen; Andrew Y. Ng; Pengfei Diao; Christian Igel; Celine M. Vachon; Katharina Holland; Rikke Rass Winkel; Nico Karssemeijer; Martin Lillholm (IEEE Trans. Medical Imaging, 2016)

Characterization of Errors in Deep Learning-Based Brain MRI Segmentation. - Akshay Pai; Yuan-Ching Teng; Joseph Blair; Michiel Kallenberg; Erik B. Dam; Stefan Sommer; Christian Igel; Mads Nielsen (Deep Learning for Medical Image Analysis, 2017)

A Strongly Quasiconvex PAC-Bayesian Bound. - Niklas Thiemann; Christian Igel; Olivier Wintenberger; Yevgeny Seldin (ALT, 2017)

Qualitative and Quantitative Assessment of Step Size Adaptation Rules. - Oswin Krause; Tobias Glasmachers; Christian Igel (FOGA, 2017)

Massively-parallel best subset selection for ordinary least-squares regression. - Fabian Gieseke; Kai Lars Polsterer; Ashish Mahabal; Christian Igel; Tom Heskes (SSCI, 2017)

Theory of Randomized Optimization Heuristics (Dagstuhl Seminar 17191). - Carola Doerr; Christian Igel; Lothar Thiele; Xin Yao 001 (Dagstuhl Reports, 2017)

Big Universe, Big Data: Machine Learning and Image Analysis for Astronomy. - Jan Kremer; Kristoffer Stensbo-Smidt; Fabian Gieseke; Kim Steenstrup Pedersen; Christian Igel (IEEE Intell. Syst., 2017)

Adaptive pattern recognition in real-time video-based soccer analysis. - Marc Schlipsing; Jan Salmen; Marc Tschentscher; Christian Igel (J. Real Time Image Process., 2017)

bufferkdtree: A Python library for massive nearest neighbor queries on multi-many-core devices. - Fabian Gieseke; Cosmin E. Oancea; Christian Igel (Knowl. Based Syst., 2017)

Editorial - Project Reports. - Christian Igel (Künstliche Intell., 2017)

Evolutionary Kernel Learning. - Christian Igel (Encyclopedia of Machine Learning and Data Mining, 2017)

Robust Active Label Correction. - Jan Kremer; Fei Sha; Christian Igel (AISTATS, 2018)

Resilient Backpropagation (Rprop) for Batch-learning in TensorFlow. - Ciprian Florescu; Christian Igel (ICLR (Workshop), 2018)

Training Big Random Forests with Little Resources. - Fabian Gieseke; Christian Igel (KDD, 2018)

Sparse Incomplete LU-Decomposition for Wave Farm Designs Under Realistic Conditions. - Dídac Rodríguez Arbonès; Nataliia Y. Sergiienko; Boyin Ding; Oswin Krause; Christian Igel; Markus Wagner 007 (PPSN (1), 2018)

Bigger Buffer k-d Trees on Multi-Many-Core Systems. - Fabian Gieseke; Cosmin Eugen Oancea; Ashish Mahabal; Christian Igel; Tom Heskes (VECPAR, 2018)

Population-Contrastive-Divergence: Does consistency help with RBM training? - Oswin Krause; Asja Fischer; Christian Igel (Pattern Recognit. Lett., 2018)

Accurate Segmentation of Dental Panoramic Radiographs with U-NETS. - Thorbjørn Louring Koch; Mathias Perslev; Christian Igel; Sami Sebastian Brandt (ISBI, 2019)

Knowledge Distillation for Semi-supervised Domain Adaptation. - Mauricio Orbes-Arteaga; M. Jorge Cardoso; Lauge Sørensen; Christian Igel; Sébastien Ourselin; Marc Modat; Mads Nielsen; Akshay Pai (OR/MLCN@MICCAI, 2019)

One Network to Segment Them All: A General, Lightweight System for Accurate 3D Medical Image Segmentation. - Mathias Perslev; Erik Bjørnager Dam; Akshay Pai; Christian Igel (MICCAI (2), 2019)

PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation. - Mauricio Orbes-Arteaga; Lauge Sørensen; Manuel Jorge Cardoso; Marc Modat; Sébastien Ourselin; Stefan Sommer; Mads Nielsen; Christian Igel; Akshay Pai (Image Processing, 2019)

U-Time: A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging. - Mathias Perslev; Michael Hejselbak Jensen; Sune Darkner; Poul Jørgen Jennum; Christian Igel (NeurIPS, 2019)

On PAC-Bayesian bounds for random forests. - Stephan Sloth Lorenzen; Christian Igel; Yevgeny Seldin (Mach. Learn., 2019)

Label-Similarity Curriculum Learning. - Ürün Dogan; Aniket Anand Deshmukh; Marcin Machura; Christian Igel (ECCV (29), 2020)

Algorithms for Estimating the Partition Function of Restricted Boltzmann Machines (Extended Abstract). - Oswin Krause; Asja Fischer; Christian Igel (IJCAI, 2020)

Do End-to-End Speech Recognition Models Care About Context? - Lasse Borgholt; Jakob D. Havtorn; Zeljko Agic; Anders Søgaard; Lars Maaløe; Christian Igel (INTERSPEECH, 2020)

A Loss Function for Generative Neural Networks Based on Watson's Perceptual Model. - Steffen Czolbe; Oswin Krause; Ingemar J. Cox; Christian Igel (NeurIPS, 2020)

Second Order PAC-Bayesian Bounds for the Weighted Majority Vote. - Andrés R. Masegosa; Stephan Sloth Lorenzen; Christian Igel; Yevgeny Seldin (NeurIPS, 2020)

Algorithms for estimating the partition function of restricted Boltzmann machines. - Oswin Krause; Asja Fischer; Christian Igel (Artif. Intell., 2020)

The International Workshop on Osteoarthritis Imaging Knee MRI Segmentation Challenge: A Multi-Institute Evaluation and Analysis Framework on a Standardized Dataset. - Arjun D. Desai; Francesco Calivá; Claudia Iriondo; Naji Khosravan; Aliasghar Mortazi; Sachin Jambawalikar; Drew A. Torigian; Jutta Ellermann; Mehmet Akçakaya; Ulas Bagci; Radhika Tibrewala; Io Flament; et al. (CoRR, 2020)

On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions. - Kai Brügge 001; Asja Fischer; Christian Igel (AISTATS, 2021)

On Scaling Contrastive Representations for Low-Resource Speech Recognition. - Lasse Borgholt; Tycho M. S. Tax; Jakob D. Havtorn; Lars Maaløe; Christian Igel (ICASSP, 2021)

Chebyshev-Cantelli PAC-Bayes-Bennett Inequality for the Weighted Majority Vote. - Yi-Shan Wu 003; Andrés R. Masegosa; Stephan Sloth Lorenzen; Christian Igel; Yevgeny Seldin (NeurIPS, 2021)

Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts. - Svetlana Kutuzova; Oswin Krause; Douglas McCloskey; Mads Nielsen; Christian Igel (CoRR, 2021)

Do We Still Need Automatic Speech Recognition for Spoken Language Understanding? - Lasse Borgholt; Jakob Drachmann Havtorn; Mostafa Abdou; Joakim Edin; Lars Maaløe; Anders Søgaard; Christian Igel (CoRR, 2021)

Machine learning for financial transaction classification across companies using character-level word embeddings of text fields. - Rasmus Kær Jørgensen; Christian Igel (Intell. Syst. Account. Finance Manag., 2021)

Data, Knowledge, and Computation. - Christian Igel (Künstliche Intell., 2021)

U-Sleep: resilient high-frequency sleep staging. - Mathias Perslev; Sune Darkner; Lykke Kempfner; Miki Nikolic; Poul Jørgen Jennum; Christian Igel (npj Digit. Medicine, 2021)

Are Multilingual Sentiment Models Equally Right for the Right Reasons? - Rasmus Kær Jørgensen; Fiammetta Caccavale; Christian Igel; Anders Søgaard (BlackboxNLP@EMNLP, 2022)

Deep learning based 3D point cloud regression for estimating forest biomass. - Stefan Oehmcke; Lei Li 050; Jaime C. Revenga; Thomas Nord-Larsen; Katerina Trepekli; Fabian Gieseke; Christian Igel (SIGSPATIAL/GIS, 2022)

Date Recognition in Historical Parish Records. - Laura Cabello Piqueras; Constanza Fierro; Jonas F. Lotz; Phillip Rust; Joen Rommedahl; Jeppe Klok Due; Christian Igel; Desmond Elliott; Carsten B. Pedersen; Israfel Salazar; Anders Søgaard (ICFHR, 2022)

Information Bottleneck: Exact Analysis of (Quantized) Neural Networks. - Stephan Sloth Lorenzen; Christian Igel; Mads Nielsen (ICLR, 2022)

Histogram-Based Unsupervised Domain Adaptation for Medical Image Classification. - Pengfei Diao; Akshay Pai; Christian Igel; Christian Hedeager Krag (MICCAI (8), 2022)

A Brief Overview of Unsupervised Neural Speech Representation Learning. - Lasse Borgholt; Jakob Drachmann Havtorn; Joakim Edin; Lars Maaløe; Christian Igel (CoRR, 2022)

Energy Consumption-Aware Tabular Benchmarks for Neural Architecture Search. - Pedram Bakhtiarifard; Christian Igel; Raghavendra Selvan (CoRR, 2022)

LR-CSNet: Low-Rank Deep Unfolding Network for Image Compressive Sensing. - Tianfang Zhang; Lei Li 050; Christian Igel; Stefan Oehmcke; Fabian Gieseke; Zhenming Peng (CoRR, 2022)

Self-Supervised Speech Representation Learning: A Review. - Abdelrahman Mohamed; Hung-yi Lee; Lasse Borgholt; Jakob D. Havtorn; Joakim Edin; Christian Igel; Katrin Kirchhoff; Shang-Wen Li 001; Karen Livescu; Lars Maaløe; Tara N. Sainath; Shinji Watanabe 001 (IEEE J. Sel. Top. Signal Process., 2022)

Above-Ground Biomass Prediction for Croplands at a Sub-Meter Resolution Using UAV-LiDAR and Machine Learning Methods. - Jaime C. Revenga; Katerina Trepekli; Stefan Oehmcke; Rasmus Jensen; Lei Li 050; Christian Igel; Fabian Gieseke; Thomas Friborg (Remote. Sens., 2022)

MultiFin: A Dataset for Multilingual Financial NLP. - Rasmus Kær Jørgensen; Oliver Brandt; Mareike Hartmann; Xiang Dai; Christian Igel; Desmond Elliott (EACL (Findings), 2023)

Predicting urban tree cover from incomplete point labels and limited background information. - Hui Zhang; Ankit Kariryaa; Venkanna Babu Guthula; Christian Igel; Stefan Oehmcke (UrbanAI@SIGSPATIAL, 2023)

BuildSeg: A General Framework for the Segmentation of Buildings. - Lei Li 050; Tianfang Zhang; Stefan Oehmcke; Fabian Gieseke; Christian Igel (CoRR, 2023)

Smooth Monotonic Networks. - Christian Igel (CoRR, 2023)

Benchmarking Individual Tree Mapping with Sub-meter Imagery. - Dimitri Gominski; Ankit Kariryaa; Martin Brandt; Christian Igel; Sizhuo Li; Maurice Mugabowindekwe; Rasmus Fensholt (CoRR, 2023)

The Liver Tumor Segmentation Benchmark (LiTS). - Patrick Bilic; Patrick Ferdinand Christ; Hongwei Li 004; Eugene Vorontsov; Avi Ben-Cohen; Georgios Kaissis; Adi Szeskin; Colin Jacobs; Gabriel Efrain Humpire Mamani; Gabriel Chartrand; Fabian Lohöfer; Julian Walter Holch; et al. (Medical Image Anal., 2023)

Remember to Correct the Bias When Using Deep Learning for Regression! - Christian Igel; Stefan Oehmcke (Künstliche Intell., 2023)

From Coarse to Fine-Grained Open-Set Recognition. - Nico Lang; Vésteinn Snæbjarnarson; Elijah Cole; Oisin Mac Aodha; Christian Igel; Serge J. Belongie (CVPR, 2024)

MMEarth: Exploring Multi-modal Pretext Tasks for Geospatial Representation Learning. - Vishal Nedungadi; Ankit Kariryaa; Stefan Oehmcke; Serge J. Belongie; Christian Igel; Nico Lang (ECCV (64), 2024)

EC-NAS: Energy Consumption Aware Tabular Benchmarks for Neural Architecture Search. - Pedram Bakhtiarifard; Christian Igel; Raghavendra Selvan (ICASSP, 2024)

Smooth Min-Max Monotonic Networks. - Christian Igel (ICML, 2024)

Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks. - Bjørn Leth Møller; Christian Igel; Kristoffer Knutsen Wickstrøm; Jon Sporring; Robert Jenssen; Bulat Ibragimov (ICML, 2024)

BMRS: Bayesian Model Reduction for Structured Pruning. - Dustin Wright 001; Christian Igel; Raghavendra Selvan (NeurIPS, 2024)

Equity through Access: A Case for Small-scale Deep Learning. - Raghavendra Selvan; Bob Pepin; Christian Igel; Gabrielle Samuel; Erik B. Dam (CoRR, 2024)

Nacala-Roof-Material: Drone Imagery for Roof Detection, Classification, and Segmentation to Support Mosquito-borne Disease Risk Assessment. - Venkanna Babu Guthula; Stefan Oehmcke; Remigio Chilaule; Hui Zhang; Nico Lang; Ankit Kariryaa; Johan Mottelson; Christian Igel (CoRR, 2024)

Bayesian vs. PAC-Bayesian Deep Neural Network Ensembles. - Nick Hauptvogel; Christian Igel (CoRR, 2024)

When Can Memorization Improve Fairness? - Bob Pepin; Christian Igel; Raghavendra Selvan (CoRR, 2024)

Fooling Contrastive Language-Image Pre-Trained Models with CLIPMasterPrints. - Matthias Freiberger; Peter Kun; Christian Igel; Anders Sundnes Løvlie; Sebastian Risi (Trans. Mach. Learn. Res., 2024)

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

Familiarity-Based Open-Set Recognition Under Adversarial Attacks. - Philip Enevoldsen; Christian Gundersen; Nico Lang; Serge J. Belongie; Christian Igel (NLDL, 2025)

NEMt: Fast Targeted Explanations for Medical Image Models via Neural Explanation Masks. - Bjørn Leth Møller; Sepideh Amiri; Christian Igel; Kristoffer Knutsen Wickstrøm; Robert Jenssen; Matthias Keicher; Mohammad Farid Azampour; Nassir Navab; Bulat Ibragimov (NLDL, 2025)

PePR: Performance Per Resource Unit as a Metric to Promote Small-scale Deep Learning. - Raghavendra Selvan; Bob Pepin; Christian Igel; Gabrielle Samuel; Erik B. Dam (NLDL, 2025)

Demosaicing and Neural Network Based Image Reconstruction in the Presence of Noise. - Gustav Emil Mark-Hansen; Frederik Henriques Altmann; Christian Igel; Ankit Kariryaa (SCIA (2), 2025)

Multi-modal classification of forest biodiversity potential from 2D orthophotos and 3D airborne laser scanning point clouds. - Simon Buus Jensen; Stefan Oehmcke; Andreas Møgelmose; Meysam Madadi; Christian Igel; Sergio Escalera; Thomas B. Moeslund (CoRR, 2025)

Climate And Resource Awareness is Imperative to Achieving Sustainable AI (and Preventing a Global AI Arms Race). - Pedram Bakhtiarifard; Pinar Tözün; Christian Igel; Raghavendra Selvan (CoRR, 2025)

Editorial. - Christian Igel (Künstliche Intell., 2025)

Efficiency Is Not Enough: A Critical Perspective on Environmentally Sustainable AI. - Dustin Wright 001; Christian Igel; Gabrielle Samuel; Raghavendra Selvan (Commun. ACM, 2025)