Theis, Lucas

22 publications

CVPR 2024 C3: High-Performance and Low-Complexity Neural Compression from a Single Image or Video Hyunjik Kim, Matthias Bauer, Lucas Theis, Jonathan Richard Schwarz, Emilien Dupont

ICML 2024 Position: What Makes an Image Realistic? Lucas Theis

ICLR 2024 The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric Daniel Severo, Lucas Theis, Jona Ballé

AISTATS 2022 Optimal Compression of Locally Differentially Private Mechanisms Abhin Shah, Wei-Ning Chen, Johannes Ballé, Peter Kairouz, Lucas Theis

ICML 2022 Algorithms for the Communication of Samples Lucas Theis, Noureldin Y Ahmed

ICLRW 2021 A Coding Theorem for the Rate-Distortion-Perception Function Lucas Theis, Aaron B. Wagner

ICLRW 2021 Importance Weighted Compression Lucas Theis, Jonathan Ho

ICLRW 2021 On the Advantages of Stochastic Encoders Lucas Theis, Eirikur Agustsson

NeurIPS 2020 Universally Quantized Neural Compression Eirikur Agustsson, Lucas Theis

NeurIPS 2019 Discriminative Topic Modeling with Logistic LDA Iryna Korshunova, Hanchen Xiong, Mateusz Fedoryszak, Lucas Theis

ICCVW 2019 HoloGAN: Unsupervised Learning of 3D Representations from Natural Images Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, Yong-Liang Yang

ICLR 2017 Amortised MAP Inference for Image Super-Resolution Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár

ICCV 2017 Fast Face-Swap Using Convolutional Neural Networks Iryna Korshunova, Wenzhe Shi, Joni Dambre, Lucas Theis

ICLR 2017 Lossy Image Compression with Compressive Autoencoders Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár

CVPR 2017 Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi

ICLR 2016 A Note on the Evaluation of Generative Models Lucas Theis, Aäron van den Oord, Matthias Bethge

ICML 2015 A Trust-Region Method for Stochastic Variational Inference with Applications to Streaming Data Lucas Theis, Matt Hoffman

AISTATS 2015 Data Modeling with the Elliptical Gamma Distribution Suvrit Sra, Reshad Hosseini, Lucas Theis, Matthias Bethge

ICLR 2015 Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet Matthias Kümmerer, Lucas Theis, Matthias Bethge

NeurIPS 2015 Generative Image Modeling Using Spatial LSTMs Lucas Theis, Matthias Bethge

NeurIPS 2012 Training Sparse Natural Image Models with a Fast Gibbs Sampler of an Extended State Space Lucas Theis, Jascha Sohl-dickstein, Matthias Bethge

JMLR 2011 In All Likelihood, Deep Belief Is Not Enough Lucas Theis, Sebastian Gerwinn, Fabian Sinz, Matthias Bethge