Tim Salimans
24 papers · 2015–2025 · 5 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (31) π Academic Marathon Β· Half π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
π
Keyword Trendsetter Combo
(5)
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Deep Specialist
(14)
π§¬
Topic Evolution
π
Keyword Champion
(2)
π§
Keyword Pioneer
π
Trend Setter
π₯
Unstoppable Β· Bronze
β
The Questioner
π
Conference Pioneer
ποΈ
Keyword Collector
(104)
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Century Club Β· Bronze
β‘
Prolific Year Β· Productive
Venues
Top co-authors
Research topics
Deep Learning
(23)
Models
(22)
Machine Learning
(14)
Computer Vision
(12)
Generation
(12)
Optimization & Theory Β· Machine Learning
(10)
Artificial Intelligence
(5)
Learning Types Β· Deep Learning
(5)
Bayesian & Probabilistic Β· Artificial Intelligence
(4)
Optimization & Theory Β· Deep Learning
(4)
Application Areas
(2)
Architectures
(2)
Bayesian & Probabilistic Β· Machine Learning
(2)
Learning Types Β· Machine Learning
(2)
Techniques
(2)
Keywords
diffusion model
(12)
image generation
(11)
knowledge distillation
(4)
generative model
(4)
stochastic gradient
(3)
variational inference
(3)
markov chain monte carlo
(3)
latent diffusion
(3)
model compression
(3)
image synthesis
(3)
model distillation
(3)
video prediction
(2)
discrete diffusion
(2)
latent space
(2)
lossless compression
(2)
generative adversarial network
(2)
generative modeling
(2)
normalizing flow
(2)
stochastic gradient descent
(2)
denoising diffusion
(2)
Papers
Simpler Diffusion: 1.5 FID on ImageNet512 with Pixel-space Diffusion
CVPR 2025
EM Distillation for One-step Diffusion Models
NeurIPS 2024
Multistep Distillation of Diffusion Models via Moment Matching
NeurIPS 2024
Rolling Diffusion Models
ICML 2024
Blurring Diffusion Models
ICLR 2023
Discrete Predictor-Corrector Diffusion Models for Image Synthesis
ICLR 2023
On Distillation of Guided Diffusion Models
CVPR 2023
simple diffusion: End-to-end diffusion for high resolution images
ICML 2023
Autoregressive Diffusion Models
ICLR 2022
Cascaded Diffusion Models for High Fidelity Image Generation
JMLR 2022
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
NeurIPS 2022
Progressive Distillation for Fast Sampling of Diffusion Models
ICLR 2022
Video Diffusion Models
NeurIPS 2022
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression
ICLR 2021
Variational Diffusion Models
NeurIPS 2021
A Spectral Energy Distance for Parallel Speech Synthesis
NeurIPS 2020
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
Improving GANs Using Optimal Transport
ICLR 2018
Improved Techniques for Training GANs
NeurIPS 2016
Improved Variational Inference with Inverse Autoregressive Flow
NeurIPS 2016
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
NeurIPS 2016
Markov Chain Monte Carlo and Variational Inference: Bridging the Gap
ICML 2015
Variational Dropout and the Local Reparameterization Trick
NeurIPS 2015