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Autoregressive Diffusion Models


Oct 05, 2021
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans


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Variational Diffusion Models


Jul 12, 2021
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho


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Agent-Centric Representations for Multi-Agent Reinforcement Learning


Apr 19, 2021
Wenling Shang, Lasse Espeholt, Anton Raichuk, Tim Salimans


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Image Super-Resolution via Iterative Refinement


Apr 15, 2021
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi


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A Spectral Energy Distance for Parallel Speech Synthesis


Aug 03, 2020
Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner


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IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression


Jun 22, 2020
Rianne van den Berg, Alexey A. Gritsenko, Mostafa Dehghani, Casper Kaae Sønderby, Tim Salimans


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Milking CowMask for Semi-Supervised Image Classification


Apr 03, 2020
Geoff French, Avital Oliver, Tim Salimans

* 10 pages, 3 figured, submitted to ICML 2020 

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MetNet: A Neural Weather Model for Precipitation Forecasting


Mar 30, 2020
Casper Kaae Sønderby, Lasse Espeholt, Jonathan Heek, Mostafa Dehghani, Avital Oliver, Tim Salimans, Shreya Agrawal, Jason Hickey, Nal Kalchbrenner


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The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks


Feb 07, 2020
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin


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How Good is the Bayes Posterior in Deep Neural Networks Really?


Feb 06, 2020
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Świątkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin


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Hydra: Preserving Ensemble Diversity for Model Distillation


Jan 14, 2020
Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton


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Axial Attention in Multidimensional Transformers


Dec 20, 2019
Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn, Tim Salimans

* 10 pages 

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Dota 2 with Large Scale Deep Reinforcement Learning


Dec 13, 2019
OpenAI, :, Christopher Berner, Greg Brockman, Brooke Chan, Vicki Cheung, Przemysław Dębiak, Christy Dennison, David Farhi, Quirin Fischer, Shariq Hashme, Chris Hesse, Rafal Józefowicz, Scott Gray, Catherine Olsson, Jakub Pachocki, Michael Petrov, Henrique Pondé de Oliveira Pinto, Jonathan Raiman, Tim Salimans, Jeremy Schlatter, Jonas Schneider, Szymon Sidor, Ilya Sutskever, Jie Tang, Filip Wolski, Susan Zhang


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Policy Gradient Search: Online Planning and Expert Iteration without Search Trees


Apr 07, 2019
Thomas Anthony, Robert Nishihara, Philipp Moritz, Tim Salimans, John Schulman


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Learning Montezuma's Revenge from a Single Demonstration


Dec 08, 2018
Tim Salimans, Richard Chen

* Deep RL Workshop, NeurIPS 2018 

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Improving GANs Using Optimal Transport


Mar 15, 2018
Tim Salimans, Han Zhang, Alec Radford, Dimitris Metaxas


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Evolution Strategies as a Scalable Alternative to Reinforcement Learning


Sep 07, 2017
Tim Salimans, Jonathan Ho, Xi Chen, Szymon Sidor, Ilya Sutskever


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Variational Lossy Autoencoder


Mar 04, 2017
Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel

* Added CIFAR10 experiments; ICLR 2017 

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Improving Variational Inference with Inverse Autoregressive Flow


Jan 30, 2017
Diederik P. Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, Max Welling


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PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications


Jan 19, 2017
Tim Salimans, Andrej Karpathy, Xi Chen, Diederik P. Kingma


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Improved Techniques for Training GANs


Jun 10, 2016
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen


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Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks


Jun 04, 2016
Tim Salimans, Diederik P. Kingma


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A Structured Variational Auto-encoder for Learning Deep Hierarchies of Sparse Features


Feb 28, 2016
Tim Salimans


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Variational Dropout and the Local Reparameterization Trick


Dec 20, 2015
Diederik P. Kingma, Tim Salimans, Max Welling


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Markov Chain Monte Carlo and Variational Inference: Bridging the Gap


May 19, 2015
Tim Salimans, Diederik P. Kingma, Max Welling


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Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression


Jul 28, 2014
Tim Salimans, David A. Knowles

* Bayesian Analysis, Volume 8, Number 4 (2013), 837-882 

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