Salimans, Tim

32 publications

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

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

NeurIPS 2024 Multistep Distillation of Diffusion Models via Moment Matching Tim Salimans, Thomas Mensink, Jonathan Heek, Emiel Hoogeboom

ICML 2024 Rolling Diffusion Models David Ruhe, Jonathan Heek, Tim Salimans, Emiel Hoogeboom

ICLR 2023 Blurring Diffusion Models Emiel Hoogeboom, Tim Salimans

ICLR 2023 Discrete Predictor-Corrector Diffusion Models for Image Synthesis Jose Lezama, Tim Salimans, Lu Jiang, Huiwen Chang, Jonathan Ho, Irfan Essa

CVPR 2023 On Distillation of Guided Diffusion Models Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans

ICML 2023 Simple Diffusion: End-to-End Diffusion for High Resolution Images Emiel Hoogeboom, Jonathan Heek, Tim Salimans

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

JMLR 2022 Cascaded Diffusion Models for High Fidelity Image Generation Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans

NeurIPSW 2022 On Distillation of Guided Diffusion Models Chenlin Meng, Ruiqi Gao, Diederik P Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans

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, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi

ICLR 2022 Progressive Distillation for Fast Sampling of Diffusion Models Tim Salimans, Jonathan Ho

NeurIPS 2022 Video Diffusion Models Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, David J Fleet

ICLRW 2022 Video Diffusion Models Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet

NeurIPSW 2021 Classifier-Free Diffusion Guidance Jonathan Ho, Tim Salimans

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

NeurIPSW 2021 Palette: Image-to-Image Diffusion Models Chitwan Saharia, William Chan, Huiwen Chang, Chris A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, Mohammad Norouzi

ICLRW 2021 Should EBMs Model the Energy or the Score? Tim Salimans, Jonathan Ho

NeurIPS 2021 Variational Diffusion Models Diederik Kingma, Tim Salimans, Ben Poole, Jonathan Ho

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

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

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

ICLRW 2019 On the Relationship Between Normalising Flows and Variational- and Denoising Autoencoders Alexey A. Gritsenko, Jasper Snoek, Tim Salimans

ICLR 2018 Improving GANs Using Optimal Transport Tim Salimans, Han Zhang, Alec Radford, Dimitris Metaxas

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

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

NeurIPS 2016 Improved Techniques for Training GANs Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen, Xi Chen

NeurIPS 2016 Improved Variational Inference with Inverse Autoregressive Flow Diederik P. Kingma, Tim Salimans, Rafal Jozefowicz, Xi Chen, Ilya Sutskever, Max Welling

NeurIPS 2016 Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks Tim Salimans, Diederik P. Kingma

ICML 2015 Markov Chain Monte Carlo and Variational Inference: Bridging the Gap Tim Salimans, Diederik Kingma, Max Welling

NeurIPS 2015 Variational Dropout and the Local Reparameterization Trick Diederik P. Kingma, Tim Salimans, Max Welling