Collaborative learning of preference rankings. - Tim Salimans; Ulrich Paquet; Thore Graepel (RecSys, 2012)

Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression - Tim Salimans; David A. Knowles (CoRR, 2012)

Observing Dark Worlds: A crowdsourcing experiment for dark matter mapping. - David R. Harvey; Thomas D. Kitching; Joyce Noah-Vanhoucke; Ben Hamner; Tim Salimans; Ana M. Pires (Astron. Comput., 2014)

Markov Chain Monte Carlo and Variational Inference: Bridging the Gap. - Tim Salimans; Diederik P. Kingma; Max Welling (ICML, 2015)

Variational Dropout and the Local Reparameterization Trick. - Diederik P. Kingma; Tim Salimans; Max Welling (NIPS, 2015)

Improving Variational Autoencoders with Inverse Autoregressive Flow. - Diederik P. Kingma; Tim Salimans; Rafal Józefowicz; Xi Chen 022; Ilya Sutskever; Max Welling (NIPS, 2016)

Improved Techniques for Training GANs. - Tim Salimans; Ian J. Goodfellow; Wojciech Zaremba; Vicki Cheung; Alec Radford; Xi Chen 022 (NIPS, 2016)

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks. - Tim Salimans; Diederik P. Kingma (NIPS, 2016)

Improving Variational Inference with Inverse Autoregressive Flow. - Diederik P. Kingma; Tim Salimans; Max Welling (CoRR, 2016)

A Structured Variational Auto-encoder for Learning Deep Hierarchies of Sparse Features. - Tim Salimans (CoRR, 2016)

Variational Lossy Autoencoder. - Xi Chen 022; Diederik P. Kingma; Tim Salimans; Yan Duan; Prafulla Dhariwal; John Schulman; Ilya Sutskever; Pieter Abbeel (ICLR (Poster), 2017)

PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications. - Tim Salimans; Andrej Karpathy; Xi Chen 022; Diederik P. Kingma (ICLR (Poster), 2017)

Evolution Strategies as a Scalable Alternative to Reinforcement Learning. - Tim Salimans; Jonathan Ho; Xi Chen 022; Ilya Sutskever (CoRR, 2017)

Improving GANs Using Optimal Transport. - Tim Salimans; Han Zhang 010; Alec Radford; Dimitris N. Metaxas (ICLR (Poster), 2018)

Learning Montezuma's Revenge from a Single Demonstration. - Tim Salimans; Richard Chen (CoRR, 2018)

On the relationship between Normalising Flows and Variational- and Denoising Autoencoders. - Alexey A. Gritsenko; Jasper Snoek; Tim Salimans (DGS@ICLR, 2019)

Policy Gradient Search: Online Planning and Expert Iteration without Search Trees. - Thomas Anthony 001; Robert Nishihara; Philipp Moritz; Tim Salimans; John Schulman (CoRR, 2019)

Dota 2 with Large Scale Deep Reinforcement Learning. - Christopher Berner; Greg Brockman; Brooke Chan; Vicki Cheung; Przemyslaw Debiak; Christy Dennison; David Farhi; Quirin Fischer; Shariq Hashme; Christopher Hesse; Rafal Józefowicz; Scott Gray; et al. (CoRR, 2019)

Axial Attention in Multidimensional Transformers. - Jonathan Ho; Nal Kalchbrenner; Dirk Weissenborn; Tim Salimans (CoRR, 2019)

The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks. - Jakub Swiatkowski; Kevin Roth; Bastiaan S. Veeling; Linh Tran; Joshua V. Dillon; Jasper Snoek; Stephan Mandt; Tim Salimans; Rodolphe Jenatton; Sebastian Nowozin (ICML, 2020)

How Good is the Bayes Posterior in Deep Neural Networks Really? - Florian Wenzel; Kevin Roth; Bastiaan S. Veeling; Jakub Swiatkowski; Linh Tran; Stephan Mandt; Jasper Snoek; Tim Salimans; Rodolphe Jenatton; Sebastian Nowozin (ICML, 2020)

A Spectral Energy Distance for Parallel Speech Synthesis. - Alexey A. Gritsenko; Tim Salimans; Rianne van den Berg; Jasper Snoek; Nal Kalchbrenner (NeurIPS, 2020)

Hydra: Preserving Ensemble Diversity for Model Distillation. - Linh Tran; Bastiaan S. Veeling; Kevin Roth; Jakub Swiatkowski; Joshua V. Dillon; Jasper Snoek; Stephan Mandt; Tim Salimans; Sebastian Nowozin; Rodolphe Jenatton (CoRR, 2020)

MetNet: A Neural Weather Model for Precipitation Forecasting. - Casper Kaae Sønderby; Lasse Espeholt; Jonathan Heek; Mostafa Dehghani 001; Avital Oliver; Tim Salimans; Shreya Agrawal; Jason Hickey; Nal Kalchbrenner (CoRR, 2020)

IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression. - Rianne van den Berg; Alexey A. Gritsenko; Mostafa Dehghani 001; Casper Kaae Sønderby; Tim Salimans (ICLR, 2021)

On Density Estimation with Diffusion Models. - Diederik P. Kingma; Tim Salimans; Ben Poole; Jonathan Ho (NeurIPS, 2021)

Agent-Centric Representations for Multi-Agent Reinforcement Learning. - Wenling Shang; Lasse Espeholt; Anton Raichuk; Tim Salimans (CoRR, 2021)

Variational Diffusion Models. - Diederik P. Kingma; Tim Salimans; Ben Poole; Jonathan Ho (CoRR, 2021)

Autoregressive Diffusion Models. - Emiel Hoogeboom; Alexey A. Gritsenko; Jasmijn Bastings; Ben Poole; Rianne van den Berg; Tim Salimans (ICLR, 2022)

Progressive Distillation for Fast Sampling of Diffusion Models. - Tim Salimans; Jonathan Ho (ICLR, 2022)

Video Diffusion Models. - Jonathan Ho; Tim Salimans; Alexey A. Gritsenko; William Chan; Mohammad Norouzi 002; David J. Fleet (NeurIPS, 2022)

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding. - 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; et al. (NeurIPS, 2022)

Palette: Image-to-Image Diffusion Models. - Chitwan Saharia; William Chan; Huiwen Chang; Chris A. Lee; Jonathan Ho; Tim Salimans; David J. Fleet; Mohammad Norouzi 002 (SIGGRAPH (Conference Paper Track), 2022)

Milking CowMask for Semi-supervised Image Classification. - Geoff French; Avital Oliver; Tim Salimans (VISIGRAPP (5: VISAPP), 2022)

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding. - Chitwan Saharia; William Chan; Saurabh Saxena; Lala Li; Jay Whang; Emily Denton; Seyed Kamyar Seyed Ghasemipour; Burcu Karagol Ayan; S. Sara Mahdavi; Raphael Gontijo Lopes; Tim Salimans; Jonathan Ho; et al. (CoRR, 2022)

Lossy Compression with Gaussian Diffusion. - Lucas Theis; Tim Salimans; Matthew D. Hoffman; Fabian Mentzer (CoRR, 2022)

Classifier-Free Diffusion Guidance. - Jonathan Ho; Tim Salimans (CoRR, 2022)

Imagen Video: High Definition Video Generation with Diffusion Models. - Jonathan Ho; William Chan; Chitwan Saharia; Jay Whang; Ruiqi Gao; Alexey A. Gritsenko; Diederik P. Kingma; Ben Poole; Mohammad Norouzi 002; David J. Fleet; Tim Salimans (CoRR, 2022)

On Distillation of Guided Diffusion Models. - Chenlin Meng; Ruiqi Gao; Diederik P. Kingma; Stefano Ermon; Jonathan Ho; Tim Salimans (CoRR, 2022)

Cascaded Diffusion Models for High Fidelity Image Generation. - Jonathan Ho; Chitwan Saharia; William Chan; David J. Fleet; Mohammad Norouzi 002; Tim Salimans (J. Mach. Learn. Res., 2022)

On Distillation of Guided Diffusion Models. - Chenlin Meng; Robin Rombach; Ruiqi Gao; Diederik P. Kingma; Stefano Ermon; Jonathan Ho; Tim Salimans (CVPR, 2023)

Blurring Diffusion Models. - Emiel Hoogeboom; Tim Salimans (ICLR, 2023)

Discrete Predictor-Corrector Diffusion Models for Image Synthesis. - José Lezama; Tim Salimans; Lu Jiang 004; Huiwen Chang; Jonathan Ho; Irfan Essa (ICLR, 2023)

simple diffusion: End-to-end diffusion for high resolution images. - Emiel Hoogeboom; Jonathan Heek; Tim Salimans (ICML, 2023)

Image Super-Resolution via Iterative Refinement. - Chitwan Saharia; Jonathan Ho; William Chan; Tim Salimans; David J. Fleet; Mohammad Norouzi 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Rolling Diffusion Models. - David Ruhe; Jonathan Heek; Tim Salimans; Emiel Hoogeboom (ICML, 2024)

Multistep Distillation of Diffusion Models via Moment Matching. - Tim Salimans; Thomas Mensink; Jonathan Heek; Emiel Hoogeboom (NeurIPS, 2024)

EM Distillation for One-step Diffusion Models. - Sirui Xie; Zhisheng Xiao; Diederik P. Kingma; Tingbo Hou; Ying Nian Wu; Kevin P. Murphy; Tim Salimans; Ben Poole; Ruiqi Gao (NeurIPS, 2024)

Multistep Consistency Models. - Jonathan Heek; Emiel Hoogeboom; Tim Salimans (CoRR, 2024)

Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion. - Emiel Hoogeboom; Thomas Mensink; Jonathan Heek; Kay Lamerigts; Ruiqi Gao; Tim Salimans (CoRR, 2024)

Simpler Diffusion: 1.5 FID on ImageNet512 with Pixel-space Diffusion. - Emiel Hoogeboom; Thomas Mensink; Jonathan Heek; Kay Lamerigts; Ruiqi Gao; Tim Salimans (CVPR, 2025)