Michael (Misha) Laskin | DeepAI

DeepAI AI Chat

Featured Co-authors

Pieter Abbeel
263 publications
Hao Liu
150 publications
Jascha Sohl-Dickstein
68 publications
Xiaofei Wang
67 publications
Alessandro Lazaric
66 publications
Satinder Singh
56 publications
Deepak Pathak
55 publications
Igor Mordatch
55 publications
Lerrel Pinto
46 publications
Aditya Grover
45 publications
Kimin Lee
42 publications

∙ 10/25/2022

In-context Reinforcement Learning with Algorithm Distillation

We propose Algorithm Distillation (AD), a method for distilling reinforc...

1 Michael (Misha) Laskin, et al. ∙

∙ 02/01/2022

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery

We introduce Contrastive Intrinsic Control (CIC), an algorithm for unsup...

1 Michael (Misha) Laskin, et al. ∙

∙ 01/31/2022

Don't Change the Algorithm, Change the Data: Exploratory Data for Offline Reinforcement Learning

Recent progress in deep learning has relied on access to large and diver...

10 Denis Yarats, et al. ∙

∙ 10/28/2021

URLB: Unsupervised Reinforcement Learning Benchmark

Deep Reinforcement Learning (RL) has emerged as a powerful paradigm to s...

15 Michael (Misha) Laskin, et al. ∙

∙ 08/11/2021

Skill Preferences: Learning to Extract and Execute Robotic Skills from Human Feedback

A promising approach to solving challenging long-horizon tasks has been ...

0 Xiaofei Wang, et al. ∙

∙ 07/19/2021

Hierarchical Few-Shot Imitation with Skill Transition Models

A desirable property of autonomous agents is the ability to both solve l...

0 Kourosh Hakhamaneshi, et al. ∙

∙ 06/16/2021

Behavioral Priors and Dynamics Models: Improving Performance and Domain Transfer in Offline RL

Offline Reinforcement Learning (RL) aims to extract near-optimal policie...

0 Catherine Cang, et al. ∙

∙ 06/02/2021

Decision Transformer: Reinforcement Learning via Sequence Modeling

We present a framework that abstracts Reinforcement Learning (RL) as a s...

0 Lili Chen, et al. ∙

∙ 12/14/2020

A Framework for Efficient Robotic Manipulation

Data-efficient learning of manipulation policies from visual observation...

8 Albert Zhan, et al. ∙

∙ 12/07/2020

Parallel Training of Deep Networks with Local Updates

Deep learning models trained on large data sets have been widely success...

8 Michael (Misha) Laskin, et al. ∙

∙ 09/14/2020

Decoupling Representation Learning from Reinforcement Learning

In an effort to overcome limitations of reward-driven feature learning i...

22 Adam Stooke, et al. ∙

∙ 07/09/2020

SUNRISE: A Simple Unified Framework for Ensemble Learning in Deep Reinforcement Learning

Model-free deep reinforcement learning (RL) has been successful in a ran...

66 Kimin Lee, et al. ∙

∙ 04/30/2020

Reinforcement Learning with Augmented Data

Learning from visual observations is a fundamental yet challenging probl...

14 Michael (Misha) Laskin, et al. ∙

∙ 04/08/2020

CURL: Contrastive Unsupervised Representations for Reinforcement Learning

We present CURL: Contrastive Unsupervised Representations for Reinforcem...

23 Aravind Srinivas, et al. ∙

∙ 03/13/2020

Sparse Graphical Memory for Robust Planning

To operate effectively in the real world, artificial agents must act fro...

17 Michael (Misha) Laskin, et al. ∙

∙ 01/08/2020

Roof Age Determination for the Automated Site-Selection of Rooftop Solar

Rooftop solar is one of the most promising tools for drawing down greenh...

1 Chris Heinrich, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world