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T. Salimans · SciRah

Researcher profile · Semantic Scholar

T. Salimans

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T. Salimans — researcher profile on SciRah

h-index: 37
Works: 61
Citations: 44K

Most-cited papers

Improved Techniques for Training GANs
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung +2 more
2016Neural Information Processing Systems11K citations
Semantic Scholar
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding
Chitwan Saharia, William Chan, Saurabh Saxena, La-La Li +10 more
2022Neural Information Processing Systems9,091 citations Open access
Semantic Scholar
Image Super-Resolution via Iterative Refinement
Chitwan Saharia, Jonathan Ho, William Chan, T. Salimans +2 more
2021IEEE Transactions on Pattern Analysis and Machine Intelligence2,749 citations Open access
Semantic Scholar
Dota 2 with Large Scale Deep Reinforcement Learning
Christopher Berner, Greg Brockman, Brooke Chan, V. Cheung +21 more
2019arXiv.org2,247 citations
Semantic Scholar
Imagen Video: High Definition Video Generation with Diffusion Models
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang +7 more
2022arXiv.org2,196 citations Open access
Semantic Scholar
Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks
T. Salimans, Diederik P. Kingma
2016Neural Information Processing Systems2,188 citations
Semantic Scholar
Improved Variational Inference with Inverse Autoregressive Flow
Diederik P. Kingma, T. Salimans, R. Józefowicz, Xi Chen +2 more
2016Neural Information Processing Systems2,069 citations
Semantic Scholar
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
T. Salimans, Jonathan Ho, Xi Chen, S. Sidor +1 more
2017arXiv.org1,871 citations
Semantic Scholar
Cascaded Diffusion Models for High Fidelity Image Generation
Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet +2 more
2021Journal of machine learning research1,731 citations
Semantic Scholar
Variational Dropout and the Local Reparameterization Trick
Diederik P. Kingma, T. Salimans, Max Welling
2015Neural Information Processing Systems1,713 citations
Semantic Scholar
PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
T. Salimans, A. Karpathy, Xi Chen, Diederik P. Kingma
2017International Conference on Learning Representations1,056 citations
Semantic Scholar
On Distillation of Guided Diffusion Models
Chenlin Meng, Robin Rombach, Rui-Qi Gao, Diederik P. Kingma +3 more
2022Computer Vision and Pattern Recognition898 citations
Semantic Scholar
Variational Lossy Autoencoder
Xi Chen, Diederik P. Kingma, T. Salimans, Yan Duan +4 more
2016International Conference on Learning Representations720 citations
Semantic Scholar
Axial Attention in Multidimensional Transformers
Jonathan Ho, N. Kalchbrenner, Dirk Weissenborn, T. Salimans
2019arXiv.org706 citations
Semantic Scholar
UvA-DARE (Digital Academic Repository) Markov Chain Monte Carlo and Variational Inference: Bridging the Gap Salimans,
T. Kingma, D. P. Welling, T. Salimans, Diederik P. Kingma
2014569 citations
Semantic Scholar
simple diffusion: End-to-end diffusion for high resolution images
E. Hoogeboom, J. Heek, T. Salimans
2023International Conference on Machine Learning494 citations Open access
Semantic Scholar
Appendix for: How Good is the Bayes Posterior in Deep Neural Networks Really?
F. Wenzel, Kevin Roth, Bastiaan S. Veeling, Jakub Swiatkowski +6 more
2020438 citations
Semantic Scholar
MetNet: A Neural Weather Model for Precipitation Forecasting
C. Sønderby, L. Espeholt, J. Heek, Mostafa Dehghani +5 more
2020arXiv.org383 citations
Semantic Scholar
Improving GANs Using Optimal Transport
T. Salimans, Han Zhang, A. Radford, Dimitris N. Metaxas
2018International Conference on Learning Representations352 citations
Semantic Scholar
Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression
T. Salimans, David A. Knowles
2012arXiv.org250 citations Open access
Semantic Scholar
Learning Montezuma's Revenge from a Single Demonstration
T. Salimans, Richard J. Chen
2018arXiv.org171 citations
Semantic Scholar
Lossy Compression with Gaussian Diffusion
L. Theis, T. Salimans, M. Hoffman, Fabian Mentzer
2022arXiv.org130 citations Open access
Semantic Scholar
Multistep Distillation of Diffusion Models via Moment Matching
T. Salimans, Thomas Mensink, J. Heek, E. Hoogeboom
2024Neural Information Processing Systems95 citations
Semantic Scholar
A Spectral Energy Distance for Parallel Speech Synthesis
A. Gritsenko, T. Salimans, Rianne van den Berg, Jasper Snoek +1 more
2020Neural Information Processing Systems89 citations
Semantic Scholar
Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion
E. Hoogeboom, Thomas Mensink, J. Heek, Kay Lamerigts +2 more
2024arXiv.org84 citations
Semantic Scholar
Multistep Consistency Models
J. Heek, E. Hoogeboom, T. Salimans
2024arXiv.org75 citations
Semantic Scholar
EM Distillation for One-step Diffusion Models
Si-Rui Xie, Zhisheng Xiao, Diederik P. Kingma, Tingbo Hou +5 more
2024Neural Information Processing Systems71 citations
Semantic Scholar
IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression
Rianne van den Berg, A. Gritsenko, Mostafa Dehghani, C. Sønderby +1 more
2020International Conference on Learning Representations71 citations
Semantic Scholar
Hydra: Preserving Ensemble Diversity for Model Distillation
Linh Tran, Bastiaan S. Veeling, Kevin Roth, Jakub Swiatkowski +6 more
2020arXiv.org67 citations
Semantic Scholar
Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions
Angana Borah, Ziwei Ji, Tiezheng Yu, Yan Xu +270 more
2024Conference on Empirical Methods in Natural Language Processing63 citations
Semantic Scholar
Milking CowMask for Semi-Supervised Image Classification
Geoff French, Avital Oliver, T. Salimans
2020VISIGRAPP61 citations Open access
Semantic Scholar
Improving Variational Autoencoders with Inverse Autoregressive Flow
Diederik P. Kingma, T. Salimans, R. Józefowicz, Xi Chen +2 more
2016Neural Information Processing Systems59 citations
Semantic Scholar
On Density Estimation with Diffusion Models
Diederik P. Kingma, T. Salimans, B. Poole, Jonathan Ho
2021Neural Information Processing Systems57 citations
Semantic Scholar
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 +6 more
2020International Conference on Machine Learning57 citations
Semantic Scholar
Discrete Predictor-Corrector Diffusion Models for Image Synthesis
José Lezama, T. Salimans, Lu Jiang, Huiwen Chang +2 more
2023International Conference on Learning Representations46 citations
Semantic Scholar
Simpler Diffusion: 1.5 FID on ImageNet512 with pixel-space diffusion
E. Hoogeboom, Thomas Mensink, J. Heek, Kay Lamerigts +2 more
2025Computer Vision and Pattern Recognition43 citations
Semantic Scholar
On Using Control Variates with Stochastic Approximation for Variational Bayes and its Connection to Stochastic Linear Regression
T. Salimans, David A. Knowles
201437 citations
Semantic Scholar
Policy Gradient Search: Online Planning and Expert Iteration without Search Trees
Thomas W. Anthony, Robert Nishihara, Philipp Moritz, T. Salimans +1 more
2019arXiv.org31 citations
Semantic Scholar
Imagen 3
Imagen-Team-Google Jason Baldridge, Jakob Bauer, Mukul Bhutani, Nicole Brichtova +254 more
202428 citations
Semantic Scholar
A Structured Variational Auto-encoder for Learning Deep Hierarchies of Sparse Features
T. Salimans
2016arXiv.org20 citations
Semantic Scholar
Unified Latents (UL): How to train your latents
J. Heek, E. Hoogeboom, Thomas Mensink, T. Salimans
2026arXiv.org19 citations
Semantic Scholar
Agent-Centric Representations for Multi-Agent Reinforcement Learning
Wen-Ling Shang, L. Espeholt, Anton Raichuk, T. Salimans
2021arXiv.org17 citations
Semantic Scholar
UvA-DARE ( Digital Academic Repository ) Markov Chain Monte Carlo and Variational Inference : Bridging the Gap
T. Salimans, Diederik P. Kingma
201416 citations
Semantic Scholar
Beyond Single Tokens: Distilling Discrete Diffusion Models via Discrete MMD
E. Hoogeboom, D. Ruhe, J. Heek, Thomas Mensink +1 more
2026arXiv.org12 citations
Semantic Scholar
On the relationship between Normalising Flows and Variational- and Denoising Autoencoders
A. Gritsenko, Jasper Snoek, T. Salimans
2019DGS@ICLR11 citations
Semantic Scholar
Implementing and Automating Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression
T. Salimans
20142 citations
Semantic Scholar
Where is Motion From? Scalable Motion Attribution for Video Generation Models
M. Albergo, N. M. Boffi, Eric Vanden-261, Juhan Bae +38 more
1 citations
Semantic Scholar
Dual-Rate Diffusion: Accelerating diffusion models with an interleaved heavy-light network
G. Bartosh, D. Ruhe, E. Hoogeboom, J. Heek +2 more
2026arXiv.org0 citations
Semantic Scholar
MUST: A Framework for Training Task-oriented Dialogue Systems with Multiple User SimulaTors
A. Radford, K. Narasimhan, T. Salimans, Jeffrey Wu +26 more
20220 citations
Semantic Scholar
On the Anatomy of Latent-variable Generative Models for Conditional Text Generation
Sophie Burkhardt, Stefan Kramer, Decoupling, Xi Chen +56 more
20220 citations
Semantic Scholar

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