Lucas Theis

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 45

Top Venues

CoRR

ICCV

AISTATS

ICLR

University of Tübingen, Germany (PHD)

Education History

University of Tübingen, Germany

PHD

Publications

Yibo Yang, Stephan Mandt, Lucas Theis
An Introduction to Neural Data Compression. Found. Trends Comput. Graph. Vis. 15 (2) (2023)
Yang Qiu, Aaron B. Wagner, Johannes Ballé, Lucas Theis
Wasserstein Distortion: Unifying Fidelity and Realism. CoRR (2023)
Emiel Hoogeboom, Eirikur Agustsson, Fabian Mentzer, Luca Versari, George Toderici, Lucas Theis
High-Fidelity Image Compression with Score-based Generative Models. CoRR (2023)
Gergely Flamich, Lucas Theis
Adaptive Greedy Rejection Sampling. ISIT (2023)
Hyunjik Kim, Matthias Bauer, Lucas Theis, Jonathan Richard Schwarz, Emilien Dupont
C3: High-performance and low-complexity neural compression from a single image or video. CoRR (2023)
Daniel Severo, Lucas Theis, Johannes Ballé
The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric. CoRR (2023)
Gergely Flamich, Lucas Theis
Adaptive Greedy Rejection Sampling. CoRR (2023)
Lucas Theis, Tim Salimans, Matthew D. Hoffman, Fabian Mentzer
Lossy Compression with Gaussian Diffusion. CoRR (2022)
Lucas Theis, Noureldin Y. Ahmed
Algorithms for the Communication of Samples. ICML (2022)
Abhin Shah, Wei-Ning Chen, Johannes Ballé, Peter Kairouz, Lucas Theis
Optimal Compression of Locally Differentially Private Mechanisms. AISTATS (2022)
Yibo Yang, Stephan Mandt, Lucas Theis
An Introduction to Neural Data Compression. CoRR (2022)
Lucas Theis, Eirikur Agustsson
On the advantages of stochastic encoders. CoRR (2021)
Abhin Shah, Wei-Ning Chen, Johannes Balle, Peter Kairouz, Lucas Theis
Optimal Compression of Locally Differentially Private Mechanisms. CoRR (2021)
Lucas Theis, Noureldin Yosri
Algorithms for the Communication of Samples. CoRR (2021)
Lucas Theis, Aaron B. Wagner
A coding theorem for the rate-distortion-perception function. CoRR (2021)
Eirikur Agustsson, Lucas Theis
Universally Quantized Neural Compression. NeurIPS (2020)
Eirikur Agustsson, Lucas Theis
Universally Quantized Neural Compression. CoRR (2020)
Iryna Korshunova, Hanchen Xiong, Mateusz Fedoryszak, Lucas Theis
Discriminative Topic Modeling with Logistic LDA. NeurIPS (2019)
Sofia Ira Ktena, Alykhan Tejani, Lucas Theis, Pranay Kumar Myana, Deepak Dilipkumar, Ferenc Huszár, Steven Yoo, Wenzhe Shi
Addressing delayed feedback for continuous training with neural networks in CTR prediction. RecSys (2019)
Sofia Ira Ktena, Alykhan Tejani, Lucas Theis, Pranay Kumar Myana, Deepak Dilipkumar, Ferenc Huszar, Steven Yoo, Wenzhe Shi
Addressing Delayed Feedback for Continuous Training with Neural Networks in CTR prediction. CoRR (2019)
Iryna Korshunova, Hanchen Xiong, Mateusz Fedoryszak, Lucas Theis
Discriminative Topic Modeling with Logistic LDA. CoRR (2019)
Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, Yong-Liang Yang
HoloGAN: Unsupervised Learning of 3D Representations From Natural Images. ICCV (2019)
Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, Yong-Liang Yang
HoloGAN: Unsupervised Learning of 3D Representations From Natural Images. ICCV Workshops (2019)
Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, Yong-Liang Yang
HoloGAN: Unsupervised learning of 3D representations from natural images. CoRR (2019)
Lucas Theis, Iryna Korshunova, Alykhan Tejani, Ferenc Huszár
Faster gaze prediction with dense networks and Fisher pruning. CoRR (2018)
Philipp Berens, Jeremy Freeman, Thomas Deneux, Nicolay Chenkov, Thomas McColgan, Artur Speiser, Jakob H. Macke, Srinivas C. Turaga, Patrick Mineault, Peter Rupprecht, Stephan Gerhard, Rainer W. Friedrich, Johannes Friedrich, Liam Paninski, Marius Pachitariu, Kenneth D. Harris, Ben Bolte, Timothy A. Machado, Dario Ringach, Jasmine Stone, Luke E. Rogerson, Nicolas J. Sofroniew, Jacob Reimer, Emmanouil Froudarakis, Thomas Euler, Miroslav Román Rosón, Lucas Theis, Andreas S. Tolias, Matthias Bethge
Community-based benchmarking improves spike rate inference from two-photon calcium imaging data. PLoS Comput. Biol. 14 (5) (2018)
Katherine Storrs, Sebastiaan Van Leuven, Steve Kojder, Lucas Theis, Ferenc Huszar
Adaptive Paired-Comparison Method for Subjective Video Quality Assessment on Mobile Devices. PCS (2018)
Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár
Amortised MAP Inference for Image Super-resolution. ICLR (2017)
Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár
Lossy Image Compression with Compressive Autoencoders. CoRR (2017)
Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew P. Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. CVPR (2017)
Andrew P. Aitken, Christian Ledig, Lucas Theis, Jose Caballero, Zehan Wang, Wenzhe Shi
Checkerboard artifact free sub-pixel convolution: A note on sub-pixel convolution, resize convolution and convolution resize. CoRR (2017)
Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár
Lossy Image Compression with Compressive Autoencoders. ICLR (Poster) (2017)
Iryna Korshunova, Wenzhe Shi, Joni Dambre, Lucas Theis
Fast Face-Swap Using Convolutional Neural Networks. ICCV (2017)
Wenzhe Shi, Jose Caballero, Lucas Theis, Ferenc Huszar, Andrew P. Aitken, Christian Ledig, Zehan Wang
Is the deconvolution layer the same as a convolutional layer? CoRR (2016)
Reshad Hosseini, Suvrit Sra, Lucas Theis, Matthias Bethge
Inference and mixture modeling with the Elliptical Gamma Distribution. Comput. Stat. Data Anal. 101 (2016)
Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár
Amortised MAP Inference for Image Super-resolution. CoRR (2016)
Lucas Theis, Aäron van den Oord, Matthias Bethge
A note on the evaluation of generative models. ICLR (2016)
Iryna Korshunova, Wenzhe Shi, Joni Dambre, Lucas Theis
Fast Face-swap Using Convolutional Neural Networks. CoRR (2016)
Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew P. Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi
Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network. CoRR (2016)
Niklas Ludtke, Debapriya Das, Lucas Theis, Matthias Bethge
A Generative Model of Natural Texture Surrogates. CoRR (2015)
Lucas Theis, Matthias Bethge
Generative Image Modeling Using Spatial LSTMs. NIPS (2015)
Lucas Theis, Matthew D. Hoffman
A trust-region method for stochastic variational inference with applications to streaming data. ICML (2015)
Matthias Kümmerer, Lucas Theis, Matthias Bethge
Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet. ICLR (Workshop) (2015)
Suvrit Sra, Reshad Hosseini, Lucas Theis, Matthias Bethge
Data modeling with the elliptical gamma distribution. AISTATS (2015)
Lucas Theis, Matthias Bethge
Generative Image Modeling Using Spatial LSTMs. CoRR (2015)
Lucas Theis, André Maia Chagas, Daniel Arnstein, Cornelius Schwarz, Matthias Bethge
Beyond GLMs: A Generative Mixture Modeling Approach to Neural System Identification. PLoS Comput. Biol. 9 (11) (2013)
Lucas Theis, Jascha Sohl-Dickstein, Matthias Bethge
Training sparse natural image models with a fast Gibbs sampler of an extended state space. NIPS (2012)
Lucas Theis, Sebastian Gerwinn, Fabian H. Sinz, Matthias Bethge
In All Likelihood, Deep Belief Is Not Enough. J. Mach. Learn. Res. 12 (2011)
Lucas Theis, Sebastian Gerwinn, Fabian H. Sinz, Matthias Bethge
In All Likelihood, Deep Belief Is Not Enough CoRR (2010)

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Publication Activity (10 Years)

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Lucas Theis