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Scott Fujimoto — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Scott Fujimoto
13
papers ·
2990
citations ·
10
h-index
Intelligent Machines (Sweden)
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Addressing Function Approximation Error in Actor-Critic Methods
2018 · 2370 citations
Off-Policy Deep Reinforcement Learning without Exploration
2018 · 280 citations
A Minimalist Approach to Offline Reinforcement Learning
2021 · 164 citations
Benchmarking Batch Deep Reinforcement Learning Algorithms
2019 · 160 citations
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay
2020 · 14 citations
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation
2021 · 2 citations
Simplicial Embeddings Improve Sample Efficiency in Actor-Critic Agents
2025
Sparse-Reg: Improving Sample Complexity in Offline Reinforcement Learning using Sparsity
2025
Towards General-Purpose Model-Free Reinforcement Learning
2025
Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank
2024
Fairness in Reinforcement Learning with Bisimulation Metrics
2024
Top co-authors
David Meger
· 5
Doina Precup
· 5
Aaron Courville
· 1
Amy Zhang
· 1
Daniel R. Jiang
· 1
Edoardo Conti
· 1
Hanna Yurchyk
· 1
Herke van Hoof
· 1
Jason D. Lee
· 1
Joelle Pineau
· 1
Johan Obando-Ceron
· 1
Michael Rabbat
· 1
Topics
Value-Based
Offline RL
Policy Gradient
Model-Based RL
Exploration
Game AI
Multi-Agent
Meta-RL
RLHF & Alignment