Matthias Bethge

According to our database1, Matthias Bethge authored at least 112 papers between 1999 and 2021.

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2021
Visual Representation Learning Does Not Generalize Strongly Within the Same Domain.
CoRR, 2021

How Well do Feature Visualizations Support Causal Understanding of CNN Activations?
CoRR, 2021

Partial success in closing the gap between human and machine vision.
CoRR, 2021

Calibrated prediction in and out-of-domain for state-of-the-art saliency modeling.
CoRR, 2021

Adapting ImageNet-scale models to complex distribution shifts with self-learning.
CoRR, 2021

State-of-the-Art in Human Scanpath Prediction.
CoRR, 2021

Pretraining boosts out-of-domain robustness for pose estimation.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2021

Contrastive Learning Inverts the Data Generating Process.
Proceedings of the 38th International Conference on Machine Learning, 2021

Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding.
Proceedings of the 9th International Conference on Learning Representations, 2021

Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Foolbox Native: Fast adversarial attacks to benchmark the robustness of machine learning models in PyTorch, TensorFlow, and JAX.
J. Open Source Softw., 2020

Closing the Generalization Gap in One-Shot Object Detection.
CoRR, 2020

Exemplary Natural Images Explain CNN Activations Better than Feature Visualizations.
CoRR, 2020

On the surprising similarities between supervised and self-supervised models.
CoRR, 2020

EagerPy: Writing Code That Works Natively with PyTorch, TensorFlow, JAX, and NumPy.
CoRR, 2020

Fast Differentiable Clipping-Aware Normalization and Rescaling.
CoRR, 2020

Unmasking the Inductive Biases of Unsupervised Object Representations for Video Sequences.
CoRR, 2020

Towards causal generative scene models via competition of experts.
CoRR, 2020

The Notorious Difficulty of Comparing Human and Machine Perception.
CoRR, 2020

Shortcut Learning in Deep Neural Networks.
CoRR, 2020

Increasing the robustness of DNNs against image corruptions by playing the Game of Noise.
CoRR, 2020

System Identification with Biophysical Constraints: A Circuit Model of the Inner Retina.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Improving robustness against common corruptions by covariate shift adaptation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Rotation-invariant clustering of neuronal responses in primary visual cortex.
Proceedings of the 8th International Conference on Learning Representations, 2020

Künstliche Intelligenz - Die dritte Welle.
Proceedings of the 50. Jahrestagung der Gesellschaft für Informatik, INFORMATIK 2020 - Back to the Future, Karlsruhe, Germany, 28. September, 2020

Measuring the Importance of Temporal Features in Video Saliency.
Proceedings of the Computer Vision - ECCV 2020, 2020

A Simple Way to Make Neural Networks Robust Against Diverse Image Corruptions.
Proceedings of the Computer Vision - ECCV 2020, 2020

2019
Deep convolutional models improve predictions of macaque V1 responses to natural images.
PLoS Comput. Biol., 2019

Learning From Brains How to Regularize Machines.
CoRR, 2019

Pretraining boosts out-of-domain robustness for pose estimation.
CoRR, 2019

Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming.
CoRR, 2019

Accurate, reliable and fast robustness evaluation.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Learning from brains how to regularize machines.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Towards the first adversarially robust neural network model on MNIST.
Proceedings of the 7th International Conference on Learning Representations, 2019

Excessive Invariance Causes Adversarial Vulnerability.
Proceedings of the 7th International Conference on Learning Representations, 2019

ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness.
Proceedings of the 7th International Conference on Learning Representations, 2019

A rotation-equivariant convolutional neural network model of primary visual cortex.
Proceedings of the 7th International Conference on Learning Representations, 2019

Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data.
PLoS Comput. Biol., 2018

One-Shot Instance Segmentation.
CoRR, 2018

Adversarial Vision Challenge.
CoRR, 2018

One-shot Texture Segmentation.
CoRR, 2018

Robust Perception through Analysis by Synthesis.
CoRR, 2018

Markerless tracking of user-defined features with deep learning.
CoRR, 2018

Trace your sources in large-scale data: one ring to find them all.
CoRR, 2018

Generalisation in humans and deep neural networks.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

One-Shot Segmentation in Clutter.
Proceedings of the 35th International Conference on Machine Learning, 2018

Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models.
Proceedings of the 6th International Conference on Learning Representations, 2018

Saliency Benchmarking Made Easy: Separating Models, Maps and Metrics.
Proceedings of the Computer Vision - ECCV 2018, 2018

Diverse Feature Visualizations Reveal Invariances in Early Layers of Deep Neural Networks.
Proceedings of the Computer Vision - ECCV 2018, 2018

2017
Signatures of criticality arise from random subsampling in simple population models.
PLoS Comput. Biol., 2017

Guiding human gaze with convolutional neural networks.
CoRR, 2017

Foolbox v0.8.0: A Python toolbox to benchmark the robustness of machine learning models.
CoRR, 2017

Saliency Benchmarking: Separating Models, Maps and Metrics.
CoRR, 2017

Comparing deep neural networks against humans: object recognition when the signal gets weaker.
CoRR, 2017

Synthesising Dynamic Textures using Convolutional Neural Networks.
CoRR, 2017

Comment on "Biologically inspired protection of deep networks from adversarial attacks".
CoRR, 2017

Neural system identification for large populations separating "what" and "where".
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

What does it take to generate natural textures?
Proceedings of the 5th International Conference on Learning Representations, 2017

Understanding Low- and High-Level Contributions to Fixation Prediction.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Methods and measurements to compare men against machines.
Proceedings of the Human Vision and Electronic Imaging 2017, Burlingame, CA, USA, 29 January 2017, 2017

Controlling Perceptual Factors in Neural Style Transfer.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016
The functional diversity of retinal ganglion cells in the mouse.
Nat., 2016

Inference and mixture modeling with the Elliptical Gamma Distribution.
Comput. Stat. Data Anal., 2016

Texture Synthesis Using Shallow Convolutional Networks with Random Filters.
CoRR, 2016

A note on the evaluation of generative models.
Proceedings of the 4th International Conference on Learning Representations, 2016

DeepGaze II: Reading fixations from deep features trained on object recognition.
CoRR, 2016

Preserving Color in Neural Artistic Style Transfer.
CoRR, 2016

Image Style Transfer Using Convolutional Neural Networks.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
A Generative Model of Natural Texture Surrogates.
CoRR, 2015

Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet.
Proceedings of the 3rd International Conference on Learning Representations, 2015

A Neural Algorithm of Artistic Style.
CoRR, 2015

Texture synthesis and the controlled generation of natural stimuli using convolutional neural networks.
CoRR, 2015

Generative Image Modeling Using Spatial LSTMs.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Texture Synthesis Using Convolutional Neural Networks.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Data modeling with the elliptical gamma distribution.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2014
Efficient Population Coding.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014

Slowness and Sparseness Have Diverging Effects on Complex Cell Learning.
PLoS Comput. Biol., 2014

How close are we to understanding image-based saliency?
CoRR, 2014

2013
Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification.
PLoS Comput. Biol., 2013

Temporal Adaptation Enhances Efficient Contrast Gain Control on Natural Images.
PLoS Comput. Biol., 2013

How Sensitive Is the Human Visual System to the Local Statistics of Natural Images?
PLoS Comput. Biol., 2013

What Is the Limit of Redundancy Reduction with Divisive Normalization?
Neural Comput., 2013

2012
A New Perceptual Bias Reveals Suboptimal Population Decoding of Sensory Responses.
PLoS Comput. Biol., 2012

Training sparse natural image models with a fast Gibbs sampler of an extended state space.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011
Gaussian process methods for estimating cortical maps.
NeuroImage, 2011

In All Likelihood, Deep Belief Is Not Enough.
J. Mach. Learn. Res., 2011

Statistical Analysis of Multi-Cell Recordings: Linking Population Coding Models to Experimental Data.
Frontiers Comput. Neurosci., 2011

2010
<i>L<sub>p</sub></i>-Nested Symmetric Distributions.
J. Mach. Learn. Res., 2010

Bayesian inference for generalized linear models for spiking neurons.
Frontiers Comput. Neurosci., 2010

Evaluating neuronal codes for inference using Fisher information.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Natural Image Coding in V1: How Much Use Is Orientation Selectivity?
PLoS Comput. Biol., 2009

Generating Spike Trains with Specified Correlation Coefficients.
Neural Comput., 2009

Characterization of the p-generalized normal distribution.
J. Multivar. Anal., 2009

Bayesian population decoding of spiking neurons.
Frontiers Comput. Neurosci., 2009

Hierarchical Modeling of Local Image Features through $L_p$-Nested Symmetric Distributions.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Bayesian estimation of orientation preference maps.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

A joint maximum-entropy model for binary neural population patterns and continuous signals.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

Neurometric function analysis of population codes.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2008
The Conjoint Effect of Divisive Normalization and Orientation Selectivity on Redundancy Reduction.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

2007
Receptive Fields without Spike-Triggering.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Bayesian Inference for Spiking Neuron Models with a Sparsity Prior.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

Near-Maximum Entropy Models for Binary Neural Representations of Natural Images.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007

The independent components of natural images are perceptually dependent.
Proceedings of the Human Vision and Electronic Imaging XII, San Jose, CA, USA, January 29, 2007

Unsupervised learning of a steerable basis for invariant image representations.
Proceedings of the Human Vision and Electronic Imaging XII, San Jose, CA, USA, January 29, 2007

Bayesian Inference for Sparse Generalized Linear Models.
Proceedings of the Machine Learning: ECML 2007, 2007

2002
Optimal Short-Term Population Coding: When Fisher Information Fails.
Neural Comput., 2002

Population coding with unreliable spikes.
Neurocomputing, 2002

Binary Tuning is Optimal for Neural Rate Coding with High Temporal Resolution.
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002

2001
Synchronous inhibition as a mechanism for unbiased selective gain control.
Neurocomputing, 2001

Spike-frequency adaptation: Phenomenological model and experimental tests.
Neurocomputing, 2001

1999
Brief pauses as signals for degressing synapses.
Neurocomputing, 1999


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