Michael Laskin

33 papers A* 10A 1Misc 1Journal 19Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	A*	`conf`	In-context Reinforcement Learning with Algorithm Distillation. ICLR Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Stenberg Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
2023	J	`jnl`	Vision-Language Models as a Source of Rewards. CoRR Kate Baumli, Satinder Baveja, Feryal M. P. Behbahani, Harris Chan, Gheorghe Comanici, Sebastian Flennerhag, Maxime Gazeau, Kristian Holsheimer, Dan Horgan, Michael Laskin, Clare Lyle, Hussain Masoom, Kay McKinney, Volodymyr Mnih, Alexander Neitz, Fabio Pardo, Jack Parker-Holder, John Quan, Tim Rocktäschel, Himanshu Sahni, Tom Schaul, Yannick Schroecker, Stephen Spencer, Richie Steigerwald, Luyu Wang, Lei Zhang
2022	J	`jnl`	CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery. CoRR Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel
2022	J	`jnl`	Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning. CoRR Denis Yarats, David Brandfonbrener, Hao Liu, Michael Laskin, Pieter Abbeel, Alessandro Lazaric, Lerrel Pinto
2022	A*	`conf`	Hierarchical Few-Shot Imitation with Skill Transition Models. ICLR Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin
2022	J	`jnl`	In-context Reinforcement Learning with Algorithm Distillation. CoRR Michael Laskin, Luyu Wang, Junhyuk Oh, Emilio Parisotto, Stephen Spencer, Richie Steigerwald, DJ Strouse, Steven Hansen, Angelos Filos, Ethan Brooks, Maxime Gazeau, Himanshu Sahni, Satinder Singh, Volodymyr Mnih
2022	A	`conf`	Learning Visual Robotic Control Efficiently with Contrastive Pre-training and Data Augmentation. IROS Albert Zhan, Ruihan Zhao, Lerrel Pinto, Pieter Abbeel, Michael Laskin
2022	A*	`conf`	Unsupervised Reinforcement Learning with Contrastive Intrinsic Control. NeurIPS Michael Laskin, Hao Liu, Xue Bin Peng, Denis Yarats, Aravind Rajeswaran, Pieter Abbeel
2021	J	`jnl`	Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL. CoRR Catherine Cang, Aravind Rajeswaran, Pieter Abbeel, Michael Laskin
2021	A*	`conf`	Decision Transformer: Reinforcement Learning via Sequence Modeling. NeurIPS Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
2021	J	`jnl`	Decision Transformer: Reinforcement Learning via Sequence Modeling. CoRR Lili Chen, Kevin Lu, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas, Igor Mordatch
2021	A*	`conf`	Decoupling Representation Learning from Reinforcement Learning. ICML Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
2021	J	`jnl`	Discrete-event modelling of the capacity of the toll collection exit point and the formation of congestion. Int. J. Simul. Process. Model. Alexander Talavirya, Michael Laskin
2021	J	`jnl`	Hierarchical Few-Shot Imitation with Skill Transition Models. CoRR Kourosh Hakhamaneshi, Ruihan Zhao, Albert Zhan, Pieter Abbeel, Michael Laskin
2021	A*	`conf`	Reinforcement Learning with Latent Flow. NeurIPS Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin
2021	J	`jnl`	Reinforcement Learning with Latent Flow. CoRR Wenling Shang, Xiaofei Wang, Aravind Srinivas, Aravind Rajeswaran, Yang Gao, Pieter Abbeel, Michael Laskin
2021	A*	`conf`	SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. ICML Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
2021	Misc	`conf`	Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback. CoRL Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin
2021	J	`jnl`	Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback. CoRR Xiaofei Wang, Kimin Lee, Kourosh Hakhamaneshi, Pieter Abbeel, Michael Laskin
2021	—	`conf`	URLB: Unsupervised Reinforcement Learning Benchmark. NeurIPS Datasets and Benchmarks Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel
2021	J	`jnl`	URLB: Unsupervised Reinforcement Learning Benchmark. CoRR Michael Laskin, Denis Yarats, Hao Liu, Kimin Lee, Albert Zhan, Kevin Lu, Catherine Cang, Lerrel Pinto, Pieter Abbeel
2020	J	`jnl`	A Framework for Efficient Robotic Manipulation. CoRR Albert Zhan, Ruihan (Philip) Zhao, Lerrel Pinto, Pieter Abbeel, Michael Laskin
2020	A*	`conf`	CURL: Contrastive Unsupervised Representations for Reinforcement Learning. ICML Michael Laskin, Aravind Srinivas, Pieter Abbeel
2020	J	`jnl`	CURL: Contrastive Unsupervised Representations for Reinforcement Learning. CoRR Aravind Srinivas, Michael Laskin, Pieter Abbeel
2020	J	`jnl`	Decoupling Representation Learning from Reinforcement Learning. CoRR Adam Stooke, Kimin Lee, Pieter Abbeel, Michael Laskin
2020	J	`jnl`	Parallel Training of Deep Networks with Local Updates. CoRR Michael Laskin, Luke Metz, Seth Nabarrao, Mark Saroufim, Badreddine Noune, Carlo Luschi, Jascha Sohl-Dickstein, Pieter Abbeel
2020	A*	`conf`	Reinforcement Learning with Augmented Data. NeurIPS Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
2020	J	`jnl`	Reinforcement Learning with Augmented Data. CoRR Michael Laskin, Kimin Lee, Adam Stooke, Lerrel Pinto, Pieter Abbeel, Aravind Srinivas
2020	J	`jnl`	Roof Age Determination for the Automated Site-Selection of Rooftop Solar. CoRR Chris Heinrich, Michael Laskin, Simas Glinskis, Evert P. L. van Nieuwenburg
2020	J	`jnl`	SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning. CoRR Kimin Lee, Michael Laskin, Aravind Srinivas, Pieter Abbeel
2020	A*	`conf`	Sparse Graphical Memory for Robust Planning. NeurIPS Scott Emmons, Ajay Jain, Michael Laskin, Thanard Kurutach, Pieter Abbeel, Deepak Pathak
2020	J	`jnl`	Sparse Graphical Memory for Robust Planning. CoRR Michael Laskin, Scott Emmons, Ajay Jain, Thanard Kurutach, Pieter Abbeel, Deepak Pathak
2018	—	`conf`	Self-Similarity for Information Flows With a Random Load Free on Distribution: the Long Memory Case. EECS Oleg Rusakov, Yuri V. Yakubovich, Michael Laskin