← Authors

Tim Salimans

24 papers · 2015–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (10) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (31) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🌍 Conference Polyglot (5) 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (10) 🌟 Keyword Trendsetter Combo (5) πŸ† Keyword Champion (3) πŸ”₯ Unstoppable (6) ⚑ Prolific Year (5) πŸš€ Conference Pioneer πŸ’Ž Century Club (24) ❓ The Questioner πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (83)

Conferences

NIPS (10) ICLR (6) ICML (5) CVPR (2) JMLR (1)

Top co-authors

Jonathan Ho (7) Emiel Hoogeboom (6) Jonathan Heek (4) Diederik P. Kingma (4) Ben Poole (3) Rianne van den Berg (3) Mohammad Norouzi (3) Jasper Snoek (3) Ruiqi Gao (3) Max Welling (3)

Keywords

diffusion model (9) image generation (8) generative model (4) model compression (3) variational inference (3) latent diffusion (3) model distillation (3) stochastic gradient (3) knowledge distillation (3) markov chain monte carlo (2) high resolution (2) bayesian neural network (2) noise schedule (2) image synthesis (2) stochastic gradient descent (2) high resolution image (2) batch normalization (1) speech synthesis (1) bayesian learning (1) video prediction (1)

Papers

Simpler Diffusion: 1.5 FID on ImageNet512 with Pixel-space Diffusion CVPR 2025
EM Distillation for One-step Diffusion Models NIPS 2024
Multistep Distillation of Diffusion Models via Moment Matching NIPS 2024
Rolling Diffusion Models ICML 2024
Blurring Diffusion Models ICLR 2023
simple diffusion: End-to-end diffusion for high resolution images ICML 2023
On Distillation of Guided Diffusion Models CVPR 2023
Discrete Predictor-Corrector Diffusion Models for Image Synthesis ICLR 2023
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding NIPS 2022
Autoregressive Diffusion Models ICLR 2022
Video Diffusion Models NIPS 2022
Cascaded Diffusion Models for High Fidelity Image Generation JMLR 2022
Progressive Distillation for Fast Sampling of Diffusion Models ICLR 2022
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression ICLR 2021
Variational Diffusion Models NIPS 2021
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML 2020
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks ICML 2020
A Spectral Energy Distance for Parallel Speech Synthesis NIPS 2020
Improving GANs Using Optimal Transport ICLR 2018
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks NIPS 2016
Improved Variational Inference with Inverse Autoregressive Flow NIPS 2016
Improved Techniques for Training GANs NIPS 2016
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap ICML 2015
Variational Dropout and the Local Reparameterization Trick NIPS 2015