Code Software Datasets Workshops & Tutorials

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	R. Geirhos, K. Narayanappa, B. Mitzkus, T. Thieringer, M. Bethge, F. A. Wichmann, and W. Brendel Partial success in closing the gap between human and machine vision Advances in Neural Information Processing Systems 34, 2021 Code, URL, BibTex
	R. Geirhos, K. Meding, and F. A. Wichmann Beyond accuracy: quantifying trial-by-trial behaviour of CNNs and humans by measuring error consistency Advances in Neural Information Processing Systems 33, 2020 Code, URL, BibTex
	R. Geirhos, P. Rubisch, C. Michaelis, M. Bethge, F. A. Wichmann, and W. Brendel ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness International Conference on Learning Representations (ICLR), 2019 Code, URL, BibTex
	A. Mathis, P. Mamidanna, K. Cury, T. Abe, V. Murthy, M. Mathis, and M. Bethge DeepLabCut: markerless pose estimation of user-defined body parts with deep learning. Nature Neuroscience, 21(9), 1281-1289, 2018 Code, URL, DOI, BibTex
	R. Geirhos, C. R. M. Temme, J. Rauber, H. H. Schütt, M. Bethge, and F. A. Wichmann Generalisation in humans and deep neural networks Advances in Neural Information Processing Systems 31, 2018 Code, URL, BibTex
	W. Brendel, J. Rauber, and M. Bethge Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models International Conference on Learning Representations, 2018 #adversarial attacks, #adversarial examples, #adversarials Code, URL, OpenReview, BibTex
	M. Kümmerer, T. S. Wallis, L. A. Gatys, and M. Bethge Understanding Low- and High-Level Contributions to Fixation Prediction The IEEE International Conference on Computer Vision (ICCV), 2017 Code, URL, PDF, model webservice, BibTex
	J. Rauber, W. Brendel, and M. Bethge Foolbox: A Python toolbox to benchmark the robustness of machine learning models Reliable Machine Learning in the Wild Workshop, 34th International Conference on Machine Learning, 2017 #adversarial attacks, #adversarial examples, #adversarials Code, URL, BibTex
	A. S. Ecker, G. H. Denfield, M. Bethge, and A. S. Tolias On the Structure of Neuronal Population Activity under Fluctuations in Attentional State Journal of Neuroscience, 36(5), 1775-1789, 2016 #attention, #gain modulation, #noise correlations, #population coding Code, URL, DOI, PDF, BibTex
	L. A. Gatys, A. S. Ecker, T. Tchumatchenko, and M. Bethge Synaptic unreliability facilitates information transmission in balanced cortical populations Physical Review E, 91(6), 62707, 2015 #synaptic noise, #balanced state, #neural population coding Code, URL, DOI, PDF, BibTex
	A. S. Ecker, P. Berens, R. J. Cotton, M. Subramaniyan, G. H. Denfield, C. R. Cadwell, S. M. Smirnakis, M. Bethge, et al. State dependence of noise correlations in macaque primary visual cortex Neuron, 82(1), 235-248, 2014 #noise correlations, #gpfa, #population, #anesthesia, #macaque Code, URL, DOI, PDF, BibTex
	L. Theis, A. M. Chagas, D. Arnstein, C. Schwarz, and M. Bethge Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification PLoS Computational Biology, 9(11), 2013 #generalized linear model, #spiking neurons, #mixture models Code, URL, DOI, PDF, BibTex
	R. M. Haefner, S. Gerwinn, J. H. Macke, and M. Bethge Inferring decoding strategies from choice probabilities in the presence of correlated variability Nature Neuroscience, 16, 235-242, 2013 #noise correlations, #choice probabilities, #decision making, #population coding Code, URL, PDF, Perspective, BibTex
	L. Theis, J. Sohl-Dickstein, and M. Bethge Training sparse natural image models with a fast Gibbs sampler of an extended state space Advances in Neural Information Processing Systems 25, 2012 #natural image statistics, #ica, #overcompleteness Code, PDF, Supplemental, Poster, BibTex
	P. Berens, A. S. Ecker, R. J. Cotton, W. J. Ma, M. Bethge, and A. S. Tolias A fast and simple population code for orientation in primate V1 Journal of Neuroscience, 32(31), 10618-10626, 2012 #population coding, #orientation, #v1, #macaque, #logistic regression, #multi-tetrode recordings, #noise correlations Code, URL, PDF, Dataset, BibTex
	L. Theis, R. Hosseini, and M. Bethge Mixtures of Conditional Gaussian Scale Mixtures Applied to Multiscale Image Representations PLoS ONE, 7(7), 2012 #natural image statistics, #gaussian scale mixtures, #random fields, #mcgsm Code, DOI, PDF, BibTex
	L. Theis, S. Gerwinn, F. Sinz, and M. Bethge In All Likelihood, Deep Belief Is Not Enough Journal of Machine Learning Research, 12, 3071-3096, 2011 #natural image statistics, #deep belief networks, #boltzmann machines, #deep learning Code, PDF, BibTex
	A. S. Ecker, P. Berens, A. S. Tolias, and M. Bethge The effect of noise correlations in populations of diversely tuned neurons The Journal of Neuroscience, 31(40), 14272-14283, 2011 #noise correlations, #population coding, #fisher information, #orientation Code, URL, DOI, PDF, BibTex
	P. Berens, A. S. Ecker, S. Gerwinn, A. S. Tolias, and M. Bethge Reassessing optimal neural population codes with neurometric functions Proceedings of the National Academy of Sciences of the United States of America, 108(11), 4423-4428, 2011 #fisher information, #population coding, #mean squared error, #discrimination error, #neurometric function Code, URL, PDF, BibTex
	S. Gerwinn, J. Macke, and M. Bethge Bayesian inference for generalized linear models for spiking neurons Frontiers in Computational Neuroscience, 4, 2010 #bayesian inference, #generalized linear model, #spiking neurons Code, URL, DOI, PDF, BibTex
	J. H. Macke, S. Gerwinn, L. White, M. Kaschube, and M. Bethge Gaussian process methods for estimating cortical maps NeuroImage, 56(2), 570-581, 2010 #gaussian process Code, URL, DOI, PDF, BibTex
	J. Eichhorn, F. Sinz, and M. Bethge Natural Image Coding in V1: How Much Use Is Orientation Selectivity? PLoS Computational Biology, 5(4), 2009 #natural image models, #natural image statistics, #normative models Code, DOI, PDF, BibTex
	J. Macke, P. Berens, A. Ecker, A. Tolias, and M. Bethge Generating Spike Trains with Specified Correlation-Coeffcients Neural Computation, 2009 #spike train, #correlated poisson, #multivariate poisson, #noise correlations, #discretized gaussian Code, PDF, BibTex
	F. H. Sinz, E. Simoncelli, and M. Bethge Hierarchical Modeling of Local Image Features through Lp-Nested Symmetric Distributions Advances in Neural Information Processing Systems 22, 2009 #natural image statistics, #ica, #lp-spherically symmetric distributions, #nu-spherical symmetric distributions Code, PDF, BibTex
	J. H. Macke, S. Gerwinn, M. Kaschube, L. E. White, and M. Bethge Bayesian estimation of orientation preference maps Advances in Neural Information Processing Systems 22, 2009 #bayesian inference, #orientation maps Code, PDF, BibTex
	S. Gerwinn, P. Berens, and M. Bethge A joint maximum-entropy model for binary neural population patterns and continuous signals Advances in Neural Information Processing Systems 22, 2009 #maximum entropy, #population coding Code, PDF, BibTex
	P. Berens, S. Gerwinn, A. S. Ecker, and M. Bethge Neurometric function analysis of population codes Advances in Neural Information Processing Systems 22, 2009 #population coding, #neurometric function Code, PDF, BibTex
	P. Berens CircStat: A Matlab Toolbox for Circular Statistics Journal of Statistical Software, 2009 #circular statistics, #directional statistics, #software, #matlab Code, URL, PDF, BibTex
	M. Bethge and P. Berens Near-Maximum Entropy Models for Binary Neural Representations of Natural Images Advances in Neural Information Processing Systems 20, 2008 #population coding, #natural image statistics, #maximum entropy Code, PDF, BibTex
	F. Sinz and M. Bethge The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction Advances in Neural Information Processing Systems 21, 2008 #contrast gain control, #normative models, #natural image statistics, #lp-spherically symmetric distributions Code, PDF, BibTex

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