Jonathan Ho

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berkeley college ∙ Stanford University

Image Super-Resolution via Iterative Refinement

We present SR3, an approach to image Super-Resolution via Repeated Refin...
04/15/2021 ∙ by Chitwan Saharia, et al. ∙ 0 ∙ share

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Denoising Diffusion Probabilistic Models

We present high quality image synthesis results using diffusion probabil...
06/19/2020 ∙ by Jonathan Ho, et al. ∙ 7 ∙ share

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Axial Attention in Multidimensional Transformers

We propose Axial Transformers, a self-attention-based autoregressive mod...
12/20/2019 ∙ by Jonathan Ho, et al. ∙ 0 ∙ share

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Compression with Flows via Local Bits-Back Coding

Likelihood-based generative models are the backbones of lossless compres...
05/21/2019 ∙ by Jonathan Ho, et al. ∙ 1 ∙ share

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Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables

The bits-back argument suggests that latent variable models can be turne...
05/16/2019 ∙ by Friso H. Kingma, et al. ∙ 11 ∙ share

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Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design

Flow-based generative models are powerful exact likelihood models with e...
02/01/2019 ∙ by Jonathan Ho, et al. ∙ 97 ∙ share

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Evolved Policy Gradients

We propose a meta-learning approach for learning gradient-based reinforc...
02/13/2018 ∙ by Rein Houthooft, et al. ∙ 0 ∙ share

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One-Shot Imitation Learning

Imitation learning has been commonly applied to solve different tasks in...
03/21/2017 ∙ by Yan Duan, et al. ∙ 0 ∙ share

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Evolution Strategies as a Scalable Alternative to Reinforcement Learning

We explore the use of Evolution Strategies (ES), a class of black box op...
03/10/2017 ∙ by Tim Salimans, et al. ∙ 0 ∙ share

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Generative Adversarial Imitation Learning

Consider learning a policy from example expert behavior, without interac...
06/10/2016 ∙ by Jonathan Ho, et al. ∙ 0 ∙ share

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Jonathan Ho

Featured Co-authors

Pieter Abbeel

Xi Chen

Stefano Ermon

Mohammad Norouzi

Ilya Sutskever

Phillip Isola

Wojciech Zaremba

William Chan

Tim Salimans

Nal Kalchbrenner

David J. Fleet

Image Super-Resolution via Iterative Refinement

Denoising Diffusion Probabilistic Models

Axial Attention in Multidimensional Transformers

Compression with Flows via Local Bits-Back Coding

Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design

Evolved Policy Gradients

One-Shot Imitation Learning

Evolution Strategies as a Scalable Alternative to Reinforcement Learning

Generative Adversarial Imitation Learning