Unifying scene registration and trajectory optimization for learning from demonstrations with application to manipulation of deformable objects. - Alex X. Lee; Sandy H. Huang; Dylan Hadfield-Menell; Eric Tzeng; Pieter Abbeel (IROS, 2014)

Beyond lowest-warping cost action selection in trajectory transfer. - Dylan Hadfield-Menell; Alex X. Lee; Chelsea Finn; Eric Tzeng; Sandy H. Huang; Pieter Abbeel (ICRA, 2015)

Leveraging appearance priors in non-rigid registration, with application to manipulation of deformable objects. - Sandy H. Huang; Jia Pan 001; George Mulcaire; Pieter Abbeel (IROS, 2015)

Adversarial Attacks on Neural Network Policies. - Sandy H. Huang; Nicolas Papernot; Ian J. Goodfellow; Yan Duan; Pieter Abbeel (ICLR (Workshop), 2017)

Expressing Robot Incapability. - Minae Kwon; Sandy H. Huang; Anca D. Dragan (HRI, 2018)

Establishing Appropriate Trust via Critical States. - Sandy H. Huang; Kush Bhatia; Pieter Abbeel; Anca D. Dragan (IROS, 2018)

Human-AI Learning Performance in Multi-Armed Bandits. - Ravi Pandya; Sandy H. Huang; Dylan Hadfield-Menell; Anca D. Dragan (AIES, 2019)

Nonverbal Robot Feedback for Human Teachers. - Sandy H. Huang; Isabella Huang; Ravi Pandya; Anca D. Dragan (CoRL, 2019)

Enabling robots to communicate their objectives. - Sandy H. Huang; David Held; Pieter Abbeel; Anca D. Dragan (Auton. Robots, 2019)

Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learning. - Sandy H. Huang; Martina Zambelli; Jackie Kay; Murilo F. Martins; Yuval Tassa; Patrick M. Pilarski; Raia Hadsell (CoRR, 2019)

A distributional view on multi-objective policy optimization. - Abbas Abdolmaleki; Sandy H. Huang; Leonard Hasenclever; Michael Neunert; H. Francis Song; Martina Zambelli; Murilo F. Martins; Nicolas Heess; Raia Hadsell; Martin A. Riedmiller (ICML, 2020)

Exploring Exploration: Comparing Children with RL Agents in Unified Environments. - Eliza Kosoy; Jasmine Collins; David M. Chan; Jessica B. Hamrick; Sandy H. Huang; Alison Gopnik; John F. Canny (CoRR, 2020)

A Constrained Multi-Objective Reinforcement Learning Framework. - Sandy H. Huang; Abbas Abdolmaleki; Giulia Vezzani; Philemon Brakel; Daniel J. Mankowitz; Michael Neunert; Steven Bohez; Yuval Tassa; Nicolas Heess; Martin A. Riedmiller; Raia Hadsell (CoRL, 2021)

On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. - Abbas Abdolmaleki; Sandy H. Huang; Giulia Vezzani; Bobak Shahriari; Jost Tobias Springenberg; Shruti Mishra; Dhruva TB; Arunkumar Byravan; Konstantinos Bousmalis; András György 001; Csaba Szepesvári; Raia Hadsell; et al. (CoRR, 2021)

Learning Causal Overhypotheses through Exploration in Children and Computational Models. - Eliza Kosoy; Adrian Liu; Jasmine Collins; David M. Chan; Jessica B. Hamrick; Nan Rosemary Ke; Sandy H. Huang; Bryanna Kaufmann; John F. Canny; Alison Gopnik (CLeaR, 2022)

Learning Causal Overhypotheses through Exploration in Children and Computational Models. - Eliza Kosoy; Adrian Liu; Jasmine Collins; David M. Chan; Jessica B. Hamrick; Sandy Han Huang; Nan Rosemary Ke; Bryanna Kaufmann; Alison Gopnik (CogSci, 2022)

Towards Understanding How Machines Can Learn Causal Overhypotheses. - Eliza Kosoy; David M. Chan; Adrian Liu; Jasmine Collins; Bryanna Kaufmann; Sandy Han Huang; Jessica B. Hamrick; John F. Canny; Nan Rosemary Ke; Alison Gopnik (CoRR, 2022)

Towards Understanding How Machines Can Learn Causal Overhypotheses. - Eliza Kosoy; David M. Chan; Adrian Liu; Jasmine Collins; Jessica B. Hamrick; Sandy Han Huang; Nan Rosemary Ke; Emily Rose Reagan; John F. Canny; Alison Gopnik (CogSci, 2023)

Coherent Soft Imitation Learning. - Joe Watson; Sandy H. Huang; Nicolas Heess (NeurIPS, 2023)

Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning. - Dhruva Tirumala; Markus Wulfmeier; Ben Moran; Sandy H. Huang; Jan Humplik; Guy Lever; Tuomas Haarnoja; Leonard Hasenclever; Arunkumar Byravan; Nathan Batchelor; Neil Sreendra; Kushal Patel; et al. (CoRL, 2024)

Replay across Experiments: A Natural Extension of Off-Policy RL. - Dhruva Tirumala; Thomas Lampe; José Enrique Chen; Tuomas Haarnoja; Sandy H. Huang; Guy Lever; Ben Moran; Tim Hertweck; Leonard Hasenclever; Martin A. Riedmiller; Nicolas Heess; Markus Wulfmeier (ICLR, 2024)

Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. - Thomas Lampe; Abbas Abdolmaleki; Sarah Bechtle; Sandy H. Huang; Jost Tobias Springenberg; Michael Bloesch; Oliver Groth; Roland Hafner; Tim Hertweck; Michael Neunert; Markus Wulfmeier; Jingwei Zhang 001; et al. (ICRA, 2024)

Imitating Language via Scalable Inverse Reinforcement Learning. - Markus Wulfmeier; Michael Bloesch; Nino Vieillard; Arun Ahuja; Jörg Bornschein; Sandy H. Huang; Artem Sokolov; Matt Barnes 001; Guillaume Desjardins; Alex Bewley; Sarah Bechtle; Jost Tobias Springenberg; et al. (NeurIPS, 2024)

Learning agile soccer skills for a bipedal robot with deep reinforcement learning. - Tuomas Haarnoja; Ben Moran; Guy Lever; Sandy H. Huang; Dhruva Tirumala; Jan Humplik; Markus Wulfmeier; Saran Tunyasuvunakool; Noah Y. Siegel; Roland Hafner; Michael Bloesch; Kristian Hartikainen; et al. (Sci. Robotics, 2024)

Data Release for: Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning. - Tuomas Haarnoja; Ben Moran; Guy Lever; Sandy H. Huang; Dhruva Tirumala; Jan Humplik; Markus Wulfmeier; Saran Tunyasuvunakool; Noah Y. Siegel; Roland Hafner; Michael Bloesch; Kristian Hartikainen; et al. (Zenodo, 2024)

Proc4Gem: Foundation models for physical agency through procedural generation. - Yixin Lin; Jan Humplik; Sandy H. Huang; Leonard Hasenclever; Francesco Romano; Stefano Saliceti; Daniel Zheng; José Enrique Chen; Catarina Barros; Adrian Collister; Matt Young; Adil Dostmohamed; et al. (CoRR, 2025)

Exploiting Policy Idling for Dexterous Manipulation. - Annie S. Chen; Philemon Brakel; Antonia Bronars; Annie Xie; Sandy H. Huang; Oliver Groth; Maria Bauzá 001; Markus Wulfmeier; Nicolas Heess; Dushyant Rao (CoRR, 2025)