Journal Articles by M. Bethge


L. Theis, P. Berens, E. Froudarakis, J. Reimer, M. Roman-Roson, T. Baden, et al.
Benchmarking spike rate inference in population calcium imaging
Neuron, 90(3), 471-482, 2016
#two-photon imaging, #spiking neurons
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A. M. Chagas, L. Theis, B. Sengupta, M. Stüttgen, M. Bethge, and C. Schwarz
Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents
Frontiers in Neural Circuits, 7(190), 2013
#neuroscience, #spiking neurons
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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, #generative modeling
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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, #random fields, #mcgsm, #mixture models
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L. Theis, S. Gerwinn, F. Sinz, and M. Bethge
In All Likelihood, Deep Belief Is Not Enough
Journal of Machine Learning Research, 12, 2011
#natural image statistics, #deep belief networks, #boltzmann machines, #deep learning
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Conference Papers


L. Theis, A. van den Oord, and M. Bethge
A note on the evaluation of generative models
International Conference on Learning Representations, 2016
#generative modeling
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L. Theis and M. Bethge
Generative Image Modeling Using Spatial LSTMs
Advances in Neural Information Processing Systems 28, 2015
#deep learning, #generative modeling, #natural image statistics, #lstm, #mcgsm
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M. Kümmerer, L. Theis, and M. Bethge
Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
ICLR Workshop, 2015
#saliency, #deep learning
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S. Sra, R. Hosseini, L. Theis, and M. Bethge
Data modeling with the elliptical gamma distribution
Artificial Intelligence and Statistics, 2015
#density estimation, #natural image statistics, #mixture modeling
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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, #bayesian inference
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Book Chapters


H. E. Gerhard, L. Theis, and M. Bethge
Modeling Natural Image Statistics
Biologically-inspired Computer Vision—Fundamentals and Applications, Wiley VCH, 2015
#natural image statistics, #mcgsm, #ica, #psychophysics
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