Tool life enhancement through nano-composite coating on the residual stress controlled cutting faces. - K. Ramesh 003; Roger Heng; Jonathan Ho; Adrian Kang (Int. J. Manuf. Technol. Manag., 2010)

Tracking deformable objects with point clouds. - John Schulman; Alex X. Lee; Jonathan Ho; Pieter Abbeel (ICRA, 2013)

Learning from Demonstrations Through the Use of Non-rigid Registration. - John Schulman; Jonathan Ho; Cameron Lee; Pieter Abbeel (ISRR, 2013)

Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization. - John Schulman; Jonathan Ho; Alex X. Lee; Ibrahim Awwal; Henry Bradlow; Pieter Abbeel (Robotics: Science and Systems, 2013)

Motion planning with sequential convex optimization and convex collision checking. - John Schulman; Yan Duan; Jonathan Ho; Alex X. Lee; Ibrahim Awwal; Henry Bradlow; Jia Pan 001; Sachin Patil; Ken Goldberg; Pieter Abbeel (Int. J. Robotics Res., 2014)

Model-Free Imitation Learning with Policy Optimization. - Jonathan Ho; Jayesh K. Gupta; Stefano Ermon (ICML, 2016)

Generative Adversarial Imitation Learning. - Jonathan Ho; Stefano Ermon (NIPS, 2016)

One-Shot Imitation Learning. - Yan Duan; Marcin Andrychowicz; Bradly C. Stadie; Jonathan Ho; Jonas Schneider 002; Ilya Sutskever; Pieter Abbeel; Wojciech Zaremba (NIPS, 2017)

Evolution Strategies as a Scalable Alternative to Reinforcement Learning. - Tim Salimans; Jonathan Ho; Xi Chen 022; Ilya Sutskever (CoRR, 2017)

Meta Learning Shared Hierarchies. - Kevin Frans; Jonathan Ho; Xi Chen 022; Pieter Abbeel; John Schulman (ICLR (Poster), 2018)

Evolved Policy Gradients. - Rein Houthooft; Yuhua Chen; Phillip Isola; Bradly C. Stadie; Filip Wolski; Jonathan Ho; Pieter Abbeel (NeurIPS, 2018)

Evolved Policy Gradients. - Rein Houthooft; Richard Y. Chen; Phillip Isola; Bradly C. Stadie; Filip Wolski; Jonathan Ho; Pieter Abbeel (CoRR, 2018)

Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design. - Jonathan Ho; Xi Chen 022; Aravind Srinivas; Yan Duan; Pieter Abbeel (ICML, 2019)

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

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

Natural Image Manipulation for Autoregressive Models Using Fisher Scores. - Wilson Yan; Jonathan Ho; Pieter Abbeel (CoRR, 2019)

Axial Attention in Multidimensional Transformers. - Jonathan Ho; Nal Kalchbrenner; Dirk Weissenborn; Tim Salimans (CoRR, 2019)

Denoising Diffusion Probabilistic Models. - Jonathan Ho; Ajay Jain; Pieter Abbeel (NeurIPS, 2020)

Deep Generative Models: Imitation Learning, Image Synthesis, and Compression - Jonathan Ho (2020)

Understanding and Segmenting Human Demonstrations into Reusable Compliant Primitives. - Elena Galbally Herrero; Jonathan Ho; Oussama Khatib (IROS, 2021)

Structured Denoising Diffusion Models in Discrete State-Spaces. - Jacob Austin; Daniel D. Johnson 001; Jonathan Ho; Daniel Tarlow; Rianne van den Berg (NeurIPS, 2021)

On Density Estimation with Diffusion Models. - Diederik P. Kingma; Tim Salimans; Ben Poole; Jonathan Ho (NeurIPS, 2021)

Learning to Efficiently Sample from Diffusion Probabilistic Models. - Daniel Watson; Jonathan Ho; Mohammad Norouzi 002; William Chan (CoRR, 2021)

Variational Diffusion Models. - Diederik P. Kingma; Tim Salimans; Ben Poole; Jonathan Ho (CoRR, 2021)

Progressive Distillation for Fast Sampling of Diffusion Models. - Tim Salimans; Jonathan Ho (ICLR, 2022)

Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality. - Daniel Watson; William Chan; Jonathan Ho; Mohammad Norouzi 002 (ICLR, 2022)

Video Diffusion Models. - Jonathan Ho; Tim Salimans; Alexey A. Gritsenko; William Chan; Mohammad Norouzi 002; David J. Fleet (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; Seyed Kamyar Seyed Ghasemipour; Raphael Gontijo Lopes; Burcu Karagol Ayan; Tim Salimans; Jonathan Ho; David J. Fleet; et al. (NeurIPS, 2022)

Palette: Image-to-Image Diffusion Models. - Chitwan Saharia; William Chan; Huiwen Chang; Chris A. Lee; Jonathan Ho; Tim Salimans; David J. Fleet; Mohammad Norouzi 002 (SIGGRAPH (Conference Paper Track), 2022)

Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding. - 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; et al. (CoRR, 2022)

Classifier-Free Diffusion Guidance. - Jonathan Ho; Tim Salimans (CoRR, 2022)

Imagen Video: High Definition Video Generation with Diffusion Models. - Jonathan Ho; William Chan; Chitwan Saharia; Jay Whang; Ruiqi Gao; Alexey A. Gritsenko; Diederik P. Kingma; Ben Poole; Mohammad Norouzi 002; David J. Fleet; Tim Salimans (CoRR, 2022)

On Distillation of Guided Diffusion Models. - Chenlin Meng; Ruiqi Gao; Diederik P. Kingma; Stefano Ermon; Jonathan Ho; Tim Salimans (CoRR, 2022)

Cascaded Diffusion Models for High Fidelity Image Generation. - Jonathan Ho; Chitwan Saharia; William Chan; David J. Fleet; Mohammad Norouzi 002; Tim Salimans (J. Mach. Learn. Res., 2022)

On Distillation of Guided Diffusion Models. - Chenlin Meng; Robin Rombach; Ruiqi Gao; Diederik P. Kingma; Stefano Ermon; Jonathan Ho; Tim Salimans (CVPR, 2023)

Discrete Predictor-Corrector Diffusion Models for Image Synthesis. - José Lezama; Tim Salimans; Lu Jiang 004; 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 002 (ICLR, 2023)

Image Super-Resolution via Iterative Refinement. - Chitwan Saharia; Jonathan Ho; William Chan; Tim Salimans; David J. Fleet; Mohammad Norouzi 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Aerodynamic optimization with large shape and topology changes using a differentiable embedded boundary method. - Jonathan Ho; Charbel Farhat (J. Comput. Phys., 2023)

Integrating Equity in Public Sector Data-Driven Decision Making: Exploring the Desired Futures of Underserved Stakeholders. - Seyun Kim; Jonathan Ho; Yinan Li; Bonnie Fan; Willa Yunqi Yang; Jessie Ramey; Sarah E. Fox; Haiyi Zhu; John Zimmerman; Motahhare Eslami (Proc. ACM Hum. Comput. Interact., 2024)