Lucas Theis
Affiliations: | Werner Reichardt Centre for Integrative Neuroscience |
Area:
Computational Neuroscience, Visual SystemGoogle:
"Lucas Theis"Mean distance: 15.8 (cluster 29) | S | N | B | C | P |
Parents
Sign in to add mentor| Matthias Bethge | grad student | 2011- | Werner Reichardt Centre for Integrative Neuroscience |
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Publications
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| Berens P, Freeman J, Deneux T, et al. (2018) Community-based benchmarking improves spike rate inference from two-photon calcium imaging data. Plos Computational Biology. 14: e1006157 |
| Theis L, Berens P, Froudarakis E, et al. (2016) Benchmarking Spike Rate Inference in Population Calcium Imaging. Neuron. 90: 471-82 |
| Hosseini R, Sra S, Theis L, et al. (2016) Inference and mixture modeling with the Elliptical Gamma Distribution Computational Statistics and Data Analysis. 101: 29-43 |
| Gerhard HE, Theis L, Bethge M. (2015) Modeling Natural Image Statistics Biologically Inspired Computer Vision: Fundamentals and Applications. 53-80 |
| Sra S, Hosseini R, Theis L, et al. (2015) Data modeling with the elliptical gamma distribution Journal of Machine Learning Research. 38: 903-911 |
| Chagas AM, Theis L, Sengupta B, et al. (2013) Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents. Frontiers in Neural Circuits. 7: 190 |
| Theis L, Chagas AM, Arnstein D, et al. (2013) Beyond GLMs: a generative mixture modeling approach to neural system identification. Plos Computational Biology. 9: e1003356 |
| Theis L, Hosseini R, Bethge M. (2012) Mixtures of conditional Gaussian scale mixtures applied to multiscale image representations. Plos One. 7: e39857 |
| Theis L, Sohl-Dickstein J, Bethge M. (2012) Training sparse natural image models with a fast Gibbs sampler of an extended state space Advances in Neural Information Processing Systems. 2: 1124-1132 |
| Theis L, Gerwinn S, Sinz F, et al. (2011) In all likelihood, deep belief is not enough Journal of Machine Learning Research. 12: 3071-3096 |