Michael (Misha) Laskin

verfied profile

∙

0 followers

∙

berkeley college

Postdoc at Berkeley AI Research in UC Berkeley working with Pieter Abbeel. Mostly focusing on unsupervised learning and deep reinforcement learning.

research

∙ 02/01/2022

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery

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

Michael (Misha) Laskin, et al. ∙

research

∙ 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...

Denis Yarats, et al. ∙

research

∙ 10/28/2021

URLB: Unsupervised Reinforcement Learning Benchmark

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

Michael (Misha) Laskin, et al. ∙

research

∙ 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 ...

Xiaofei Wang, et al. ∙

research

∙ 07/19/2021

Hierarchical Few-Shot Imitation with Skill Transition Models

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

Kourosh Hakhamaneshi, et al. ∙

research

∙ 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...

Catherine Cang, et al. ∙

research

∙ 06/02/2021

Decision Transformer: Reinforcement Learning via Sequence Modeling

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

Lili Chen, et al. ∙

research

∙ 12/14/2020

A Framework for Efficient Robotic Manipulation

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

Albert Zhan, et al. ∙

research

∙ 12/07/2020

Parallel Training of Deep Networks with Local Updates

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

Michael (Misha) Laskin, et al. ∙

research

∙ 09/14/2020

Decoupling Representation Learning from Reinforcement Learning

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

Adam Stooke, et al. ∙

research

∙ 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...

Kimin Lee, et al. ∙

research

∙ 04/30/2020

Reinforcement Learning with Augmented Data

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

Michael (Misha) Laskin, et al. ∙

research

∙ 04/08/2020

CURL: Contrastive Unsupervised Representations for Reinforcement Learning

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

Aravind Srinivas, et al. ∙

research

∙ 03/13/2020

Sparse Graphical Memory for Robust Planning

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

Michael (Misha) Laskin, et al. ∙

research

∙ 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...

Chris Heinrich, et al. ∙

Michael (Misha) Laskin

Featured Co-authors

Pieter Abbeel

Hao Liu

Jascha Sohl-Dickstein

Alessandro Lazaric

Xiaofei Wang

Igor Mordatch

Deepak Pathak

Lerrel Pinto

Aditya Grover

Kimin Lee

Luke Metz

CIC: Contrastive Intrinsic Control for Unsupervised Skill Discovery

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

URLB: Unsupervised Reinforcement Learning Benchmark

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

Hierarchical Few-Shot Imitation with Skill Transition Models

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

Decision Transformer: Reinforcement Learning via Sequence Modeling

A Framework for Efficient Robotic Manipulation

Parallel Training of Deep Networks with Local Updates

Decoupling Representation Learning from Reinforcement Learning

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

Reinforcement Learning with Augmented Data

CURL: Contrastive Unsupervised Representations for Reinforcement Learning

Sparse Graphical Memory for Robust Planning

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