Tim Salimans
24 papers · 2015–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (5) 🏃 Academic Marathon (10) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐝 Cross-Pollinator (10)
🌍
Conference Polyglot
(5)
🐣
Hot Topic Early Bird
🏃
Academic Marathon
(10)
🌟
Keyword Trendsetter Combo
(5)
🏆
Keyword Champion
(3)
🔥
Unstoppable
(6)
⚡
Prolific Year
(5)
🚀
Conference Pioneer
💎
Century Club
(24)
❓
The Questioner
📈
Trend Setter
🗃️
Keyword Collector
(83)
Conferences
NIPS (10)
ICLR (6)
ICML (5)
CVPR (2)
JMLR (1)
Top co-authors
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