Lucas Theis

发表

HoloGAN: Unsupervised Learning of 3D Representations From Natural Images

Yong-Liang Yang, Thu Nguyen-Phuoc, Chuan Li, 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).

Neural Adaptation as Bayesian Inference

Matthias Bethge, Lucas Theis, T Farzami, 2013 .

Data modeling with the elliptical gamma distribution

Matthias Bethge, Suvrit Sra, Reshad Hosseini, 2015, AISTATS.

Supervised learning sets benchmark for robust spike detection from calcium imaging signals

Matthias Bethge, Emmanouil Froudarakis, Andreas S. Tolias, 2015 .

Standardizing and benchmarking data analysis for calcium imaging

Matthias Bethge, Andreas S. Tolias, Lucas Theis, 2017 .

Advances in probabilistic modeling of natural images

Lucas Theis, Lucas Theis, 2015 .

Amortised MAP Inference for Image Super-resolution pdf

Lucas Theis, Casper Kaae Sønderby, Wenzhe Shi, 2016, ICLR.

In All Likelihood, Deep Belief Is Not Enough

Matthias Bethge, Lucas Theis, Sebastian Gerwinn, 2010, J. Mach. Learn. Res..

Adaptive Paired-Comparison Method for Subjective Video Quality Assessment on Mobile Devices

Sebastiaan Van Leuven, Lucas Theis, Ferenc Huszar, 2018, 2018 Picture Coding Symposium (PCS).

Likelihood Estimation in Deep Belief Networks

Matthias Bethge, Lucas Theis, Sebastian Gerwinn, 2010 .

A generative model of natural images as patchworks of textures

Matthias Bethge, Lucas Theis, Debapriya Das, 2013 .

Community-based benchmarking improves spike inference from two-photon calcium imaging data

Matthias Bethge, Andreas S. Tolias, Jakob H. Macke, 2017, bioRxiv.

Addressing delayed feedback for continuous training with neural networks in CTR prediction

Lucas Theis, Alykhan Tejani, Sofia Ira Ktena, 2019, RecSys.

Supervised learning sets benchmark for robust spike rate inference from calcium imaging signals

Matthias Bethge, Emmanouil Froudarakis, Lucas Theis, 2015, bioRxiv.

Is the deconvolution layer the same as a convolutional layer? pdf

Christian Ledig, Lucas Theis, Zehan Wang, 2016, ArXiv.

Community-based benchmarking improves spike rate inference from two-photon calcium imaging data

Kenneth D. Harris, Matthias Bethge, Emmanouil Froudarakis, 2018, PLoS Comput. Biol..

Universally Quantized Neural Compression pdf

Eirikur Agustsson, Lucas Theis, Lucas Theis, 2020, NeurIPS.

Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize pdf

Christian Ledig, Lucas Theis, Zehan Wang, 2017, ArXiv.

Lossy Image Compression with Compressive Autoencoders pdf

Lucas Theis, Andrew Cunningham, Wenzhe Shi, 2017, ICLR.

Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification

Matthias Bethge, Lucas Theis, Cornelius Schwarz, 2012, PLoS Comput. Biol..

Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet pdf

Matthias Bethge, Lucas Theis, Matthias Kümmerer, 2014, ICLR.

Training sparse natural image models with a fast Gibbs sampler of an extended state space

Matthias Bethge, Jascha Sohl-Dickstein, Lucas Theis, 2012, NIPS.

A Generative Model of Natural Texture Surrogates pdf

Matthias Bethge, Lucas Theis, Debapriya Das, 2015, ArXiv.

Fast Face-Swap Using Convolutional Neural Networks

Lucas Theis, Joni Dambre, Wenzhe Shi, 2016, 2017 IEEE International Conference on Computer Vision (ICCV).

A note on the evaluation of generative models pdf

Matthias Bethge, Lucas Theis, Aäron van den Oord, 2015, ICLR.

A trust-region method for stochastic variational inference with applications to streaming data

Matthew D. Hoffman, Lucas Theis, M. Hoffman, 2015, ICML.

A multiscale model of natural images

Matthias Bethge, Reshad Hosseini, Lucas Theis, 2011 .

Modeling Natural Image Statistics

Matthias Bethge, Lucas Theis, Holly E. Gerhard, 2015 .

Generative Image Modeling Using Spatial LSTMs

Matthias Bethge, Lucas Theis, M. Bethge, 2015, NIPS.

Beyond GLMs: a generative mixture modeling approach to neural system identification

Matthias Bethge, Lucas Theis, Cornelius Schwarz, 2012 .

Faster gaze prediction with dense networks and Fisher pruning pdf

Lucas Theis, Alykhan Tejani, Iryna Korshunova, 2018, ArXiv.

Benchmarking Spike Rate Inference in Population Calcium Imaging

Matthias Bethge, Emmanouil Froudarakis, Jacob Reimer, 2016, Neuron.

HoloGAN: Unsupervised Learning of 3D Representations From Natural Images

Thu Nguyen-Phuoc, Lucas Theis, Christian Richardt, 2019, 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW).

Discriminative Topic Modeling with Logistic LDA

Hanchen Xiong, Lucas Theis, Iryna Korshunova, 2019, NeurIPS.

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

Christian Ledig, Lucas Theis, Alykhan Tejani, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

On the advantages of stochastic encoders pdf

Eirikur Agustsson, Lucas Theis, Lucas Theis, 2021, ArXiv.

Optimal Compression of Locally Differentially Private Mechanisms pdf

Lucas Theis, Peter Kairouz, Abhin Shah, 2021, ArXiv.

A coding theorem for the rate-distortion-perception function pdf

Lucas Theis, Aaron B. Wagner, Lucas Theis, 2021, ArXiv.

Algorithms for the Communication of Samples pdf

Lucas Theis, Noureldin Yosri, 2021, ArXiv.

Functional analysis of ultra high information rates conveyed by rat vibrissal primary afferents

Matthias Bethge, Maik C. Stüttgen, Lucas Theis, 2013, Front. Neural Circuits.

Statistical inference with the Elliptical Gamma Distribution

Matthias Bethge, Suvrit Sra, Reshad Hosseini, 2014 .