Jonathan Ho

56 papers A* 16A 1C 1Journal 32Unranked 5
YearRankTypeTitle / Venue / Authors
2024 J jnl
Integrating Equity in Public Sector Data-Driven Decision Making: Exploring the Desired Futures of Underserved Stakeholders.
Proc. ACM Hum. Comput. Interact.
Seyun Kim, Jonathan Ho, Yinan Li, Bonnie Fan, Willa Yunqi Yang, Jessie Ramey, Sarah E. Fox, Haiyi Zhu, John Zimmerman, Motahhare Eslami
2023 J jnl
Aerodynamic optimization with large shape and topology changes using a differentiable embedded boundary method.
J. Comput. Phys.
Jonathan Ho, Charbel Farhat
2023 A* conf
Discrete Predictor-Corrector Diffusion Models for Image Synthesis.
ICLR
José Lezama, Tim Salimans, Lu Jiang, Huiwen Chang, Jonathan Ho, Irfan Essa
2023 J jnl
Image Super-Resolution via Iterative Refinement.
IEEE Trans. Pattern Anal. Mach. Intell.
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
2023 A* conf
Novel View Synthesis with Diffusion Models.
ICLR
Daniel Watson, William Chan, Ricardo Martin-Brualla, Jonathan Ho, Andrea Tagliasacchi, Mohammad Norouzi
2023 A* conf
On Distillation of Guided Diffusion Models.
CVPR
Chenlin Meng, Robin Rombach, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
2022 J jnl
Cascaded Diffusion Models for High Fidelity Image Generation.
J. Mach. Learn. Res.
Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans
2022 J jnl
Classifier-Free Diffusion Guidance.
CoRR
Jonathan Ho, Tim Salimans
2022 J jnl
Imagen Video: High Definition Video Generation with Diffusion Models.
CoRR
Jonathan Ho, William Chan, Chitwan Saharia, Jay Whang, Ruiqi Gao, Alexey A. Gritsenko, Diederik P. Kingma, Ben Poole, Mohammad Norouzi, David J. Fleet, Tim Salimans
2022 A* conf
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality.
ICLR
Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi
2022 J jnl
Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality.
CoRR
Daniel Watson, William Chan, Jonathan Ho, Mohammad Norouzi
2022 J jnl
Novel View Synthesis with Diffusion Models.
CoRR
Daniel Watson, William Chan, Ricardo Martin-Brualla, Jonathan Ho, Andrea Tagliasacchi, Mohammad Norouzi
2022 J jnl
On Distillation of Guided Diffusion Models.
CoRR
Chenlin Meng, Ruiqi Gao, Diederik P. Kingma, Stefano Ermon, Jonathan Ho, Tim Salimans
2022 — conf
Palette: Image-to-Image Diffusion Models.
SIGGRAPH (Conference Paper Track)
Chitwan Saharia, William Chan, Huiwen Chang, Chris A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, Mohammad Norouzi
2022 A* conf
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.
NeurIPS
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L. Denton, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, Jonathan Ho, David J. Fleet, Mohammad Norouzi
2022 J jnl
Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding.
CoRR
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S. Sara Mahdavi, Raphael Gontijo Lopes, Tim Salimans, Jonathan Ho, David J. Fleet, Mohammad Norouzi
2022 A* conf
Progressive Distillation for Fast Sampling of Diffusion Models.
ICLR
Tim Salimans, Jonathan Ho
2022 J jnl
Progressive Distillation for Fast Sampling of Diffusion Models.
CoRR
Tim Salimans, Jonathan Ho
2022 A* conf
Video Diffusion Models.
NeurIPS
Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet
2022 J jnl
Video Diffusion Models.
CoRR
Jonathan Ho, Tim Salimans, Alexey A. Gritsenko, William Chan, Mohammad Norouzi, David J. Fleet
2021 J jnl
Cascaded Diffusion Models for High Fidelity Image Generation.
CoRR
Jonathan Ho, Chitwan Saharia, William Chan, David J. Fleet, Mohammad Norouzi, Tim Salimans
2021 J jnl
Image Super-Resolution via Iterative Refinement.
CoRR
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J. Fleet, Mohammad Norouzi
2021 J jnl
Learning to Efficiently Sample from Diffusion Probabilistic Models.
CoRR
Daniel Watson, Jonathan Ho, Mohammad Norouzi, William Chan
2021 A* conf
On Density Estimation with Diffusion Models.
NeurIPS
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
2021 J jnl
Palette: Image-to-Image Diffusion Models.
CoRR
Chitwan Saharia, William Chan, Huiwen Chang, Chris A. Lee, Jonathan Ho, Tim Salimans, David J. Fleet, Mohammad Norouzi
2021 A* conf
Structured Denoising Diffusion Models in Discrete State-Spaces.
NeurIPS
Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
2021 J jnl
Structured Denoising Diffusion Models in Discrete State-Spaces.
CoRR
Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, Rianne van den Berg
2021 A conf
Understanding and Segmenting Human Demonstrations into Reusable Compliant Primitives.
IROS
Elena Galbally Herrero, Jonathan Ho, Oussama Khatib
2021 J jnl
Variational Diffusion Models.
CoRR
Diederik P. Kingma, Tim Salimans, Ben Poole, Jonathan Ho
2020 — —
Deep Generative Models: Imitation Learning, Image Synthesis, and Compression
Jonathan Ho
2020 A* conf
Denoising Diffusion Probabilistic Models.
NeurIPS
Jonathan Ho, Ajay Jain, Pieter Abbeel
2020 J jnl
Denoising Diffusion Probabilistic Models.
CoRR
Jonathan Ho, Ajay Jain, Pieter Abbeel
2019 J jnl
Axial Attention in Multidimensional Transformers.
CoRR
Jonathan Ho, Nal Kalchbrenner, Dirk Weissenborn, Tim Salimans
2019 A* conf
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables.
ICML
Friso H. Kingma, Pieter Abbeel, Jonathan Ho
2019 J jnl
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables.
CoRR
Friso H. Kingma, Pieter Abbeel, Jonathan Ho
2019 A* conf
Compression with Flows via Local Bits-Back Coding.
NeurIPS
Jonathan Ho, Evan Lohn, Pieter Abbeel
2019 J jnl
Compression with Flows via Local Bits-Back Coding.
CoRR
Jonathan Ho, Evan Lohn, Pieter Abbeel
2019 A* conf
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design.
ICML
Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel
2019 J jnl
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design.
CoRR
Jonathan Ho, Xi Chen, Aravind Srinivas, Yan Duan, Pieter Abbeel
2019 J jnl
Natural Image Manipulation for Autoregressive Models Using Fisher Scores.
CoRR
Wilson Yan, Jonathan Ho, Pieter Abbeel
2018 A* conf
Evolved Policy Gradients.
NeurIPS
Rein Houthooft, Yuhua Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel
2018 J jnl
Evolved Policy Gradients.
CoRR
Rein Houthooft, Richard Y. Chen, Phillip Isola, Bradly C. Stadie, Filip Wolski, Jonathan Ho, Pieter Abbeel
2018 — conf
Meta Learning Shared Hierarchies.
ICLR (Poster)
Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, John Schulman
2017 J jnl
Evolution Strategies as a Scalable Alternative to Reinforcement Learning.
CoRR
Tim Salimans, Jonathan Ho, Xi Chen, Ilya Sutskever
2017 J jnl
Meta Learning Shared Hierarchies.
CoRR
Kevin Frans, Jonathan Ho, Xi Chen, Pieter Abbeel, John Schulman
2017 — conf
One-Shot Imitation Learning.
NIPS
Yan Duan, Marcin Andrychowicz, Bradly C. Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba
2017 J jnl
One-Shot Imitation Learning.
CoRR
Yan Duan, Marcin Andrychowicz, Bradly C. Stadie, Jonathan Ho, Jonas Schneider, Ilya Sutskever, Pieter Abbeel, Wojciech Zaremba
2016 — conf
Generative Adversarial Imitation Learning.
NIPS
Jonathan Ho, Stefano Ermon
2016 J jnl
Generative Adversarial Imitation Learning.
CoRR
Jonathan Ho, Stefano Ermon
2016 A* conf
Model-Free Imitation Learning with Policy Optimization.
ICML
Jonathan Ho, Jayesh K. Gupta, Stefano Ermon
2016 J jnl
Model-Free Imitation Learning with Policy Optimization.
CoRR
Jonathan Ho, Jayesh K. Gupta, Stefano Ermon
2014 J jnl
Motion planning with sequential convex optimization and convex collision checking.
Int. J. Robotics Res.
John Schulman, Yan Duan, Jonathan Ho, Alex X. Lee, Ibrahim Awwal, Henry Bradlow, Jia Pan, Sachin Patil, Ken Goldberg, Pieter Abbeel
2013 — conf
Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization.
Robotics: Science and Systems
John Schulman, Jonathan Ho, Alex X. Lee, Ibrahim Awwal, Henry Bradlow, Pieter Abbeel
2013 C conf
Learning from Demonstrations Through the Use of Non-rigid Registration.
ISRR
John Schulman, Jonathan Ho, Cameron Lee, Pieter Abbeel
2013 A* conf
Tracking deformable objects with point clouds.
ICRA
John Schulman, Alex X. Lee, Jonathan Ho, Pieter Abbeel
2010 J jnl
Tool life enhancement through nano-composite coating on the residual stress controlled cutting faces.
Int. J. Manuf. Technol. Manag.
K. Ramesh, Roger Heng, Jonathan Ho, Adrian Kang