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ORCIDSandy H. Huang
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2020 – today
- 2024
[j2]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, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess:
Learning agile soccer skills for a bipedal robot with deep reinforcement learning. Sci. Robotics 9(89) (2024)- [c17]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:
Replay across Experiments: A Natural Extension of Off-Policy RL. ICLR 2024 - [c16]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, Francesco Nori, Nicolas Heess, Martin A. Riedmiller:
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. ICRA 2024: 7772-7779 - [i18]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, Marlon Gwira, Francesco Nori, Martin A. Riedmiller, Nicolas Heess:
Learning Robot Soccer from Egocentric Vision with Deep Reinforcement Learning. CoRR abs/2405.02425 (2024) - [i17]Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jorg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Maria Elisabeth Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller:
Imitating Language via Scalable Inverse Reinforcement Learning. CoRR abs/2409.01369 (2024) - 2023
- [c15]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:
Towards Understanding How Machines Can Learn Causal Overhypotheses. CogSci 2023 - [c14]Joe Watson, Sandy H. Huang, Nicolas Heess:
Coherent Soft Imitation Learning. NeurIPS 2023 - [i16]Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Markus Wulfmeier, Jan Humplik, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess:
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning. CoRR abs/2304.13653 (2023) - [i15]Joe Watson, Sandy H. Huang, Nicolas Heess:
Coherent Soft Imitation Learning. CoRR abs/2305.16498 (2023) - [i14]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:
Replay across Experiments: A Natural Extension of Off-Policy RL. CoRR abs/2311.15951 (2023) - [i13]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, Francesco Nori, Nicolas Heess, Martin A. Riedmiller:
Mastering Stacking of Diverse Shapes with Large-Scale Iterative Reinforcement Learning on Real Robots. CoRR abs/2312.11374 (2023) - 2022
- [c13]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:
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CLeaR 2022: 390-406 - [c12]Eliza Kosoy, Adrian Liu, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy Han Huang, Nan Rosemary Ke, Bryanna Kaufmann, Alison Gopnik:
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CogSci 2022 - [i12]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:
Learning Causal Overhypotheses through Exploration in Children and Computational Models. CoRR abs/2202.10430 (2022) - [i11]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:
Towards Understanding How Machines Can Learn Causal Overhypotheses. CoRR abs/2206.08353 (2022) - 2021
- [c11]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:
A Constrained Multi-Objective Reinforcement Learning Framework. CoRL 2021: 883-893 - [i10]Abbas Abdolmaleki, Sandy H. Huang, Giulia Vezzani, Bobak Shahriari, Jost Tobias Springenberg, Shruti Mishra, Dhruva TB, Arunkumar Byravan, Konstantinos Bousmalis, András György, Csaba Szepesvári, Raia Hadsell, Nicolas Heess, Martin A. Riedmiller:
On Multi-objective Policy Optimization as a Tool for Reinforcement Learning. CoRR abs/2106.08199 (2021) - 2020
- [c10]Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller:
A distributional view on multi-objective policy optimization. ICML 2020: 11-22 - [i9]Eliza Kosoy, Jasmine Collins, David M. Chan, Jessica B. Hamrick, Sandy H. Huang, Alison Gopnik, John F. Canny:
Exploring Exploration: Comparing Children with RL Agents in Unified Environments. CoRR abs/2005.02880 (2020) - [i8]Abbas Abdolmaleki, Sandy H. Huang, Leonard Hasenclever, Michael Neunert, H. Francis Song, Martina Zambelli, Murilo F. Martins, Nicolas Heess, Raia Hadsell, Martin A. Riedmiller:
A Distributional View on Multi-Objective Policy Optimization. CoRR abs/2005.07513 (2020)
2010 – 2019
- 2019
- [j1]Sandy H. Huang, David Held, Pieter Abbeel, Anca D. Dragan:
Enabling robots to communicate their objectives. Auton. Robots 43(2): 309-326 (2019) - [c9]Ravi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, Anca D. Dragan:
Human-AI Learning Performance in Multi-Armed Bandits. AIES 2019: 369-375 - [c8]Sandy H. Huang, Isabella Huang, Ravi Pandya, Anca D. Dragan:
Nonverbal Robot Feedback for Human Teachers. CoRL 2019: 1038-1051 - [i7]Sandy H. Huang, Martina Zambelli, Jackie Kay, Murilo F. Martins, Yuval Tassa, Patrick M. Pilarski, Raia Hadsell:
Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learning. CoRR abs/1903.08542 (2019) - [i6]Sandy H. Huang, Isabella Huang, Ravi Pandya, Anca D. Dragan:
Nonverbal Robot Feedback for Human Teachers. CoRR abs/1911.02320 (2019) - 2018
- [c7]Minae Kwon, Sandy H. Huang, Anca D. Dragan:
Expressing Robot Incapability. HRI 2018: 87-95 - [c6]Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan:
Establishing Appropriate Trust via Critical States. IROS 2018: 3929-3936 - [i5]Minae Kwon, Sandy H. Huang, Anca D. Dragan:
Expressing Robot Incapability. CoRR abs/1810.08167 (2018) - [i4]Sandy H. Huang, Kush Bhatia, Pieter Abbeel, Anca D. Dragan:
Establishing Appropriate Trust via Critical States. CoRR abs/1810.08174 (2018) - [i3]Ravi Pandya, Sandy H. Huang, Dylan Hadfield-Menell, Anca D. Dragan:
Human-AI Learning Performance in Multi-Armed Bandits. CoRR abs/1812.09376 (2018) - 2017
- [c5]Sandy H. Huang, Nicolas Papernot, Ian J. Goodfellow, Yan Duan, Pieter Abbeel:
Adversarial Attacks on Neural Network Policies. ICLR (Workshop) 2017 - [c4]Sandy H. Huang, David Held, Pieter Abbeel, Anca D. Dragan:
Enabling Robots to Communicate Their Objectives. Robotics: Science and Systems 2017 - [i2]Sandy H. Huang, Nicolas Papernot, Ian J. Goodfellow, Yan Duan, Pieter Abbeel:
Adversarial Attacks on Neural Network Policies. CoRR abs/1702.02284 (2017) - [i1]Sandy H. Huang, David Held, Pieter Abbeel, Anca D. Dragan:
Enabling Robots to Communicate their Objectives. CoRR abs/1702.03465 (2017) - 2015
- [c3]Dylan Hadfield-Menell, Alex X. Lee, Chelsea Finn, Eric Tzeng, Sandy H. Huang, Pieter Abbeel:
Beyond lowest-warping cost action selection in trajectory transfer. ICRA 2015: 3231-3238 - [c2]Sandy H. Huang, Jia Pan, George Mulcaire, Pieter Abbeel:
Leveraging appearance priors in non-rigid registration, with application to manipulation of deformable objects. IROS 2015: 878-885 - 2014
- [c1]Alex X. Lee, Sandy H. Huang, Dylan Hadfield-Menell, Eric Tzeng, Pieter Abbeel:
Unifying scene registration and trajectory optimization for learning from demonstrations with application to manipulation of deformable objects. IROS 2014: 4402-4407
Coauthor Index
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