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Trevor Darrell — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Trevor Darrell
65
papers ·
20637
citations ·
139
h-index
University of California, Berkeley
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Large-Scale Study of Curiosity-Driven Learning
2018 · 367 citations
Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees
2018 · 101 citations
Reinforcement Learning from Imperfect Demonstrations
2018 · 99 citations
Loss is its own Reward: Self-Supervision for Reinforcement Learning
2016 · 91 citations
Guiding Pretraining in Reinforcement Learning with Large Language Models
2023 · 39 citations
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning
2019 · 21 citations
Regularization Matters in Policy Optimization
2019 · 18 citations
Explaining Reinforcement Learning Policies through Counterfactual Trajectories
2022 · 3 citations
Real-World Humanoid Locomotion with Reinforcement Learning
2023 · 3 citations
Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer
2016 · 1 citations
Zero-shot Policy Learning with Spatial Temporal RewardDecomposition on Contingency-aware Observation
2019
Teachable Reinforcement Learning via Advice Distillation
2022
Top co-authors
Pieter Abbeel
· 4
Olivia Watkins
· 3
Abhishek Gupta
· 2
Huazhe Xu
· 2
Jacob Andreas
· 2
Sergey Levine
· 2
Abhishek Gupta
· 1
Alexei A. Efros
· 1
Allan Jabri
· 1
Amos Storkey
· 1
Bike Zhang
· 1
Bingyi Kang
· 1
Topics
Meta-RL
Exploration
Value-Based
Model-Based RL
Game AI
Offline RL
Multi-Agent
Policy Gradient
Safe RL
RLHF & Alignment