Ho, Jonathan

23 publications

ICLR 2023 Discrete Predictor-Corrector Diffusion Models for Image Synthesis Jose Lezama, Tim Salimans, Lu Jiang, Huiwen Chang, Jonathan Ho, Irfan Essa

ICLR 2023 Novel View Synthesis with Diffusion Models Daniel Watson, William Chan, Ricardo Martin Brualla, Jonathan Ho, Andrea Tagliasacchi, Mohammad Norouzi

CVPR 2023 On Distillation of Guided Diffusion Models Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans

JMLR 2022 Cascaded Diffusion Models for High Fidelity Image Generation Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans

ICLR 2022 Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi

NeurIPSW 2022 On Distillation of Guided Diffusion Models Chenlin Meng, Ruiqi Gao, Diederik P Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans

NeurIPS 2022 Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J Fleet, Mohammad Norouzi

ICLR 2022 Progressive Distillation for Fast Sampling of Diffusion Models Tim Salimans, Jonathan Ho

NeurIPS 2022 Video Diffusion Models Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, David J Fleet

ICLRW 2022 Video Diffusion Models Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet

NeurIPSW 2021 Classifier-Free Diffusion Guidance Jonathan Ho, Tim Salimans

ICLRW 2021 Importance Weighted Compression Lucas Theis, Jonathan Ho

NeurIPSW 2021 Palette: Image-to-Image Diffusion Models Chitwan Saharia, William Chan, Huiwen Chang, Chris A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, Mohammad Norouzi

ICLRW 2021 Should EBMs Model the Energy or the Score? Tim Salimans, Jonathan Ho

NeurIPS 2021 Structured Denoising Diffusion Models in Discrete State-Spaces Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg

NeurIPS 2021 Variational Diffusion Models Diederik Kingma, Tim Salimans, Ben Poole, Jonathan Ho

NeurIPS 2020 Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay N. Jain, Pieter Abbeel

ICML 2019 Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables Friso Kingma, Pieter Abbeel, Jonathan Ho

NeurIPS 2019 Compression with Flows via Local Bits-Back Coding Jonathan Ho, Evan Lohn, Pieter Abbeel

ICML 2019 Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel

ICLR 2018 Meta Learning Shared Hierarchies Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, John Schulman

NeurIPS 2016 Generative Adversarial Imitation Learning Jonathan Ho, Stefano Ermon

ICML 2016 Model-Free Imitation Learning with Policy Optimization Jonathan Ho, Jayesh Gupta, Stefano Ermon