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Nando de Freitas — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Nando de Freitas
31
papers ·
2377
citations ·
59
h-index
Google (United States)
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Most-cited papers
Learning to Communicate with Deep Multi-Agent Reinforcement Learning
2016 · 871 citations
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
2018 · 264 citations
Sample Efficient Actor-Critic with Experience Replay
2016 · 222 citations
Reinforcement and Imitation Learning for Diverse Visuomotor Skills
2018 · 215 citations
Critic Regularized Regression
2020 · 90 citations
Acme: A Research Framework for Distributed Reinforcement Learning
2020 · 73 citations
Learning to Perform Physics Experiments via Deep Reinforcement Learning
2016 · 55 citations
Scaling data-driven robotics with reward sketching and batch reinforcement learning
2019 · 45 citations
Hyperparameter Selection for Offline Reinforcement Learning
2020 · 43 citations
Making Efficient Use of Demonstrations to Solve Hard Exploration Problems
2019 · 24 citations
Reinforced Self-Training (ReST) for Language Modeling
2023 · 18 citations
Offline Learning from Demonstrations and Unlabeled Experience
2020 · 14 citations
Learning Compositional Neural Programs with Recursive Tree Search and Planning
2019 · 13 citations
Semi-supervised reward learning for offline reinforcement learning
2020 · 7 citations
Playing hard exploration games by watching YouTube
2018 · 6 citations
Top co-authors
Caglar Gulcehre
· 11
Ziyu Wang
· 10
Tom Le Paine
· 8
Alexander Novikov
· 5
Scott Reed
· 5
Bobak Shahriari
· 4
Sergio G\'omez Colmenarejo
· 4
Yutian Chen
· 4
Arnaud Doucet
· 3
Nicolas Heess
· 3
Srivatsan Srinivasan
· 3
Arthur Gretton
· 2
Topics
Offline RL
Value-Based
Model-Based RL
Safe RL
Game AI
Exploration
Multi-Agent
Policy Gradient
Meta-RL
RLHF & Alignment