Tim Salimans

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 62

Top Topics

Variational Inference

Lossy Compression

Top Venues

Publications

Sirui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou, Ying Nian Wu, Kevin Patrick Murphy, Tim Salimans, Ben Poole, Ruiqi Gao
EM Distillation for One-step Diffusion Models. CoRR (2024)
Tim Salimans, Thomas Mensink, Jonathan Heek, Emiel Hoogeboom
Multistep Distillation of Diffusion Models via Moment Matching. CoRR (2024)
Jonathan Heek, Emiel Hoogeboom, Tim Salimans
Multistep Consistency Models. CoRR (2024)
David Ruhe, Jonathan Heek, Tim Salimans, Emiel Hoogeboom
Rolling Diffusion Models. CoRR (2024)
José Lezama, Tim Salimans, Lu Jiang, Huiwen Chang, Jonathan Ho, Irfan Essa
Discrete Predictor-Corrector Diffusion Models for Image Synthesis. ICLR (2023)
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
Image Super-Resolution via Iterative Refinement. IEEE Trans. Pattern Anal. Mach. Intell. 45 (4) (2023)
Emiel Hoogeboom, Tim Salimans
Blurring Diffusion Models. ICLR (2023)
Emiel Hoogeboom, Jonathan Heek, Tim Salimans
simple diffusion: End-to-end diffusion for high resolution images. ICML (2023)
Emiel Hoogeboom, Jonathan Heek, Tim Salimans
simple diffusion: End-to-end diffusion for high resolution images. CoRR (2023)
Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
On Distillation of Guided Diffusion Models. CVPR (2023)
Lucas Theis, Tim Salimans, Matthew D. Hoffman, Fabian Mentzer
Lossy Compression with Gaussian Diffusion. CoRR (2022)
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J. Fleet, Mohammad Norouzi
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding. CoRR (2022)
Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet
Video Diffusion Models. CoRR (2022)
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans
Autoregressive Diffusion Models. ICLR (2022)
Tim Salimans, Jonathan Ho
Progressive Distillation for Fast Sampling of Diffusion Models. ICLR (2022)
Emiel Hoogeboom, Tim Salimans
Blurring Diffusion Models. CoRR (2022)
Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans
Cascaded Diffusion Models for High Fidelity Image Generation. J. Mach. Learn. Res. 23 (2022)
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey A. Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, Tim Salimans
Imagen Video: High Definition Video Generation with Diffusion Models. CoRR (2022)
Tim Salimans, Jonathan Ho
Progressive Distillation for Fast Sampling of Diffusion Models. CoRR (2022)
Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet
Video Diffusion Models. NeurIPS (2022)
Geoff French, Avital Oliver, Tim Salimans
Milking CowMask for Semi-supervised Image Classification. VISIGRAPP (5: VISAPP) (2022)
Chenlin Meng, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
On Distillation of Guided Diffusion Models. CoRR (2022)
Chitwan Saharia, William Chan, Huiwen Chang, Chris A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, Mohammad Norouzi
Palette: Image-to-Image Diffusion Models. SIGGRAPH (Conference Paper Track) (2022)
Jonathan Ho, Tim Salimans
Classifier-Free Diffusion Guidance. CoRR (2022)
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L. Denton, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, Mohammad Norouzi
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding. NeurIPS (2022)
Wenling Shang, Lasse Espeholt, Anton Raichuk, Tim Salimans
Agent-Centric Representations for Multi-Agent Reinforcement Learning. CoRR (2021)
Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans
Cascaded Diffusion Models for High Fidelity Image Generation. CoRR (2021)
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
Variational Diffusion Models. CoRR (2021)
Emiel Hoogeboom, Alexey A. Gritsenko, Jasmijn Bastings, Ben Poole, Rianne van den Berg, Tim Salimans
Autoregressive Diffusion Models. CoRR (2021)
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
Image Super-Resolution via Iterative Refinement. CoRR (2021)
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
On Density Estimation with Diffusion Models. NeurIPS (2021)
Rianne van den Berg, Alexey A. Gritsenko, Mostafa Dehghani, Casper Kaae Sønderby, Tim Salimans
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression. ICLR (2021)
Chitwan Saharia, William Chan, Huiwen Chang, Chris A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, Mohammad Norouzi
Palette: Image-to-Image Diffusion Models. CoRR (2021)
Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner
A Spectral Energy Distance for Parallel Speech Synthesis. NeurIPS (2020)
Alexey A. Gritsenko, Tim Salimans, Rianne van den Berg, Jasper Snoek, Nal Kalchbrenner
A Spectral Energy Distance for Parallel Speech Synthesis. CoRR (2020)
Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Sebastian Nowozin, Rodolphe Jenatton
Hydra: Preserving Ensemble Diversity for Model Distillation. CoRR (2020)
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. CoRR (2020)
Rianne van den Berg, Alexey A. Gritsenko, Mostafa Dehghani, Casper Kaae Sønderby, Tim Salimans
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression. CoRR (2020)
Casper Kaae Sønderby, Lasse Espeholt, Jonathan Heek, Mostafa Dehghani, Avital Oliver, Tim Salimans, Shreya Agrawal, Jason Hickey, Nal Kalchbrenner
MetNet: A Neural Weather Model for Precipitation Forecasting. CoRR (2020)
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling, Linh Tran, Joshua V. Dillon, Jasper Snoek, Stephan Mandt, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. ICML (2020)
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML (2020)
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski, Linh Tran, Stephan Mandt, Jasper Snoek, Tim Salimans, Rodolphe Jenatton, Sebastian Nowozin
How Good is the Bayes Posterior in Deep Neural Networks Really? CoRR (2020)
Geoff French, Avital Oliver, Tim Salimans
Milking CowMask for Semi-Supervised Image Classification. CoRR (2020)
Thomas Anthony, Robert Nishihara, Philipp Moritz, Tim Salimans, John Schulman
Policy Gradient Search: Online Planning and Expert Iteration without Search Trees. CoRR (2019)
Christopher Berner, Greg Brockman, Brooke Chan, Vicki Cheung, Przemyslaw Debiak, Christy Dennison, David Farhi, Quirin Fischer, Shariq Hashme, Christopher 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
Dota 2 with Large Scale Deep Reinforcement Learning. CoRR (2019)
Alexey A. Gritsenko, Jasper Snoek, Tim Salimans
On the relationship between Normalising Flows and Variational- and Denoising Autoencoders. DGS@ICLR (2019)
Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn, Tim Salimans
Axial Attention in Multidimensional Transformers. CoRR (2019)
Tim Salimans, Han Zhang, Alec Radford, Dimitris N. Metaxas
Improving GANs Using Optimal Transport. ICLR (Poster) (2018)
Tim Salimans, Han Zhang, Alec Radford, Dimitris N. Metaxas
Improving GANs Using Optimal Transport. CoRR (2018)
Tim Salimans, Richard Chen
Learning Montezuma's Revenge from a Single Demonstration. CoRR (2018)
Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel
Variational Lossy Autoencoder. ICLR (Poster) (2017)
Tim Salimans, Andrej Karpathy, Xi Chen, Diederik P. Kingma
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications. CoRR (2017)
Tim Salimans, Andrej Karpathy, Xi Chen, Diederik P. Kingma
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications. ICLR (Poster) (2017)
Tim Salimans, Jonathan Ho, Xi Chen, Ilya Sutskever
Evolution Strategies as a Scalable Alternative to Reinforcement Learning. CoRR (2017)
Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
Improved Techniques for Training GANs. CoRR (2016)
Diederik P. Kingma, Tim Salimans, Max Welling
Improving Variational Inference with Inverse Autoregressive Flow. CoRR (2016)
Tim Salimans, Diederik P. Kingma
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks. NIPS (2016)
Tim Salimans
A Structured Variational Auto-encoder for Learning Deep Hierarchies of Sparse Features. CoRR (2016)
Diederik P. Kingma, Tim Salimans, Rafal Józefowicz, Xi Chen, Ilya Sutskever, Max Welling
Improving Variational Autoencoders with Inverse Autoregressive Flow. NIPS (2016)
Tim Salimans, Ian J. Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen
Improved Techniques for Training GANs. NIPS (2016)
Xi Chen, Diederik P. Kingma, Tim Salimans, Yan Duan, Prafulla Dhariwal, John Schulman, Ilya Sutskever, Pieter Abbeel
Variational Lossy Autoencoder. CoRR (2016)
Tim Salimans, Diederik P. Kingma
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks. CoRR (2016)
Tim Salimans, Diederik P. Kingma, Max Welling
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap. ICML (2015)
Diederik P. Kingma, Tim Salimans, Max Welling
Variational Dropout and the Local Reparameterization Trick. CoRR (2015)
David R. Harvey, Thomas D. Kitching, Joyce Noah-Vanhoucke, Ben Hamner, Tim Salimans, Ana M. Pires
Observing Dark Worlds: A crowdsourcing experiment for dark matter mapping. Astron. Comput. 5 (2014)
Tim Salimans, David A. Knowles
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression CoRR (2012)
Tim Salimans, Ulrich Paquet, Thore Graepel
Collaborative learning of preference rankings. RecSys (2012)