Proceedings of the SIGGRAPH '22: Special Interest Group on Computer Graphics and Interactive Techniques Conference, Vancouver, BC, Canada, August 7, 2022

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.

[BibT_eX]

[DOI]

Chitwan Saharia

Seyed Kamyar Seyed Ghasemipour

Raphael Gontijo Lopes

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Video Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Progressive Distillation for Fast Sampling of Diffusion Models.

[BibT_eX]

[DOI]

Tim Salimans

Jonathan Ho

Proceedings of the Tenth International Conference on Learning Representations, 2022

Autoregressive Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Variational Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2021

Agent-Centric Representations for Multi-Agent Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

On Density Estimation with Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

IDF++: Analyzing and Improving Integer Discrete Flows for Lossless Compression.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

MetNet: A Neural Weather Model for Precipitation Forecasting.

[BibT_eX]

[DOI]

CoRR, 2020

Hydra: Preserving Ensemble Diversity for Model Distillation.

[BibT_eX]

[DOI]

CoRR, 2020

A Spectral Energy Distance for Parallel Speech Synthesis.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

How Good is the Bayes Posterior in Deep Neural Networks Really?

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Axial Attention in Multidimensional Transformers.

[BibT_eX]

[DOI]

CoRR, 2019

Dota 2 with Large Scale Deep Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2019

Policy Gradient Search: Online Planning and Expert Iteration without Search Trees.

[BibT_eX]

[DOI]

CoRR, 2019

On the relationship between Normalising Flows and Variational- and Denoising Autoencoders.

[BibT_eX]

[DOI]

Alexey A. Gritsenko

Jasper Snoek

Tim Salimans

Proceedings of the Deep Generative Models for Highly Structured Data, 2019

2018

Learning Montezuma's Revenge from a Single Demonstration.

[BibT_eX]

[DOI]

Tim Salimans

Richard Chen

CoRR, 2018

Improving GANs Using Optimal Transport.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Evolution Strategies as a Scalable Alternative to Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2017

PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

Variational Lossy Autoencoder.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

A Structured Variational Auto-encoder for Learning Deep Hierarchies of Sparse Features.

[BibT_eX]

[DOI]

Tim Salimans

CoRR, 2016

Improving Variational Inference with Inverse Autoregressive Flow.

[BibT_eX]

[DOI]

Diederik P. Kingma

Tim Salimans

Max Welling

CoRR, 2016

Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks.

[BibT_eX]

[DOI]

Tim Salimans

Diederik P. Kingma

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Improved Techniques for Training GANs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Improving Variational Autoencoders with Inverse Autoregressive Flow.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Variational Dropout and the Local Reparameterization Trick.

[BibT_eX]

[DOI]

Diederik P. Kingma

Tim Salimans

Max Welling

Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Markov Chain Monte Carlo and Variational Inference: Bridging the Gap.

[BibT_eX]

[DOI]

Tim Salimans

Diederik P. Kingma

Max Welling

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Observing Dark Worlds: A crowdsourcing experiment for dark matter mapping.

[BibT_eX]

[DOI]

Astron. Comput., 2014

2012

Fixed-Form Variational Posterior Approximation through Stochastic Linear Regression

[BibT_eX]

[DOI]

Tim Salimans

David A. Knowles

CoRR, 2012

Collaborative learning of preference rankings.

[BibT_eX]

[DOI]

Tim Salimans

Ulrich Paquet

Thore Graepel

Proceedings of the Sixth ACM Conference on Recommender Systems, 2012

Tim Salimans

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