Michael Chang - RankMe

22 papers A* 6B 1Misc 1Journal 11Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. ICLR Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang
2023	A*	`conf`	Im-Promptu: In-Context Composition from Image Prompts. NeurIPS Bhishma Dedhia, Michael Chang, Jake Snell, Tom Griffiths, Niraj K. Jha
2023	J	`jnl`	Im-Promptu: In-Context Composition from Image Prompts. CoRR Bhishma Dedhia, Michael Chang, Jake C. Snell, Thomas L. Griffiths, Niraj K. Jha
2023	J	`jnl`	Neural Constraint Satisfaction: Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. CoRR Michael Chang, Alyssa L. Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang
2023	—	`—`	Neural Software Abstractions Michael Chang
2022	A*	`conf`	Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation. NeurIPS Michael Chang, Tom Griffiths, Sergey Levine
2022	J	`jnl`	Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation. CoRR Michael Chang, Thomas L. Griffiths, Sergey Levine
2021	J	`jnl`	Explore and Control with Adversarial Surprise. CoRR Arnaud Fickinger, Natasha Jaques, Samyak Parajuli, Michael Chang, Nicholas Rhinehart, Glen Berseth, Stuart Russell, Sergey Levine
2021	A*	`conf`	Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment. ICML Michael Chang, Sidhant Kaushik, Sergey Levine, Tom Griffiths
2021	J	`jnl`	Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment. CoRR Michael Chang, Sidhant Kaushik, Sergey Levine, Thomas L. Griffiths
2020	A*	`conf`	Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions. ICML Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Tom Griffiths, Sergey Levine
2020	J	`jnl`	Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions. CoRR Michael Chang, Sidhant Kaushik, S. Matthew Weinberg, Thomas L. Griffiths, Sergey Levine
2019	—	`conf`	Automatically Composing Representation Transformations as a Means for Generalization. ICLR (Poster) Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths
2019	Misc	`conf`	Entity Abstraction in Visual Model-Based Reinforcement Learning. CoRL Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine
2019	J	`jnl`	Entity Abstraction in Visual Model-Based Reinforcement Learning. CoRR Rishi Veerapaneni, John D. Co-Reyes, Michael Chang, Michael Janner, Chelsea Finn, Jiajun Wu, Joshua B. Tenenbaum, Sergey Levine
2019	A*	`conf`	MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies. NeurIPS Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine
2019	J	`jnl`	MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies. CoRR Xue Bin Peng, Michael Chang, Grace Zhang, Pieter Abbeel, Sergey Levine
2018	J	`jnl`	Automatically Composing Representation Transformations as a Means for Generalization. CoRR Michael Chang, Abhishek Gupta, Sergey Levine, Thomas L. Griffiths
2018	B	`conf`	Representational efficiency outweighs action efficiency in human program induction. CogSci Sophia Sanborn, David Bourgin, Michael Chang, Tom Griffiths
2018	J	`jnl`	Representational efficiency outweighs action efficiency in human program induction. CoRR Sophia Sanborn, David D. Bourgin, Michael Chang, Thomas L. Griffiths
2017	—	`conf`	A Compositional Object-Based Approach to Learning Physical Dynamics. ICLR (Poster) Michael Chang, Tomer D. Ullman, Antonio Torralba, Joshua B. Tenenbaum
2016	J	`jnl`	Understanding Visual Concepts with Continuation Learning. CoRR William F. Whitney, Michael Chang, Tejas D. Kulkarni, Joshua B. Tenenbaum