Scott Fujimoto

Publication Activity (10 Years)

Years Active: 2018-2023
Publications (10 Years): 22

Top Topics

Geometric Structure

Exploration Exploitation

Reinforcement Learning

Top Venues

Publications

Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Shane Gu, Doina Precup, David Meger
For SALE: State-Action Representation Learning for Deep Reinforcement Learning. CoRR (2023)
Wei-Di Chang, Scott Fujimoto, David Meger, Gregory Dudek
Imitation Learning from Observation through Optimal Transport. CoRR (2023)
Scott Fujimoto, Wei-Di Chang, Edward J. Smith, Shixiang Gu, Doina Precup, David Meger
For SALE: State-Action Representation Learning for Deep Reinforcement Learning. NeurIPS (2023)
Wei-Di Chang, Juan Camilo Gamboa Higuera, Scott Fujimoto, David Meger, Gregory Dudek
IL-flOw: Imitation Learning from Observation using Normalizing Flows. CoRR (2022)
Scott Fujimoto, David Meger, Doina Precup, Ofir Nachum, Shixiang Shane Gu
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error. CoRR (2022)
Scott Fujimoto, David Meger, Doina Precup, Ofir Nachum, Shixiang Shane Gu
Why Should I Trust You, Bellman? The Bellman Error is a Poor Replacement for Value Error. ICML (2022)
Scott Fujimoto, David Meger, Doina Precup
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation. ICML (2021)
Scott Fujimoto, Shixiang Shane Gu
A Minimalist Approach to Offline Reinforcement Learning. NeurIPS (2021)
Scott Fujimoto, Shixiang Shane Gu
A Minimalist Approach to Offline Reinforcement Learning. CoRR (2021)
Scott Fujimoto, David Meger, Doina Precup
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation. CoRR (2021)
Scott Fujimoto, David Meger, Doina Precup
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay. CoRR (2020)
Scott Fujimoto, David Meger, Doina Precup
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay. NeurIPS (2020)
Scott Fujimoto, David Meger, Doina Precup
Off-Policy Deep Reinforcement Learning without Exploration. ICML (2019)
Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau
Benchmarking Batch Deep Reinforcement Learning Algorithms. CoRR (2019)
Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. ICML (2019)
Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. CoRR (2019)
Scott Fujimoto, David Meger, Doina Precup
Off-Policy Deep Reinforcement Learning without Exploration. CoRR (2018)
Kian Kenyon-Dean, Eisha Ahmed, Scott Fujimoto, Jeremy Georges-Filteau, Christopher Glasz, Barleen Kaur, Auguste Lalande, Shruti Bhanderi, Robert Belfer, Nirmal Kanagasabai, Roman Sarrazingendron, Rohit Verma, Derek Ruths
Sentiment Analysis: It's Complicated! NAACL-HLT (2018)
Edward J. Smith, Scott Fujimoto, David Meger
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation. NeurIPS (2018)
Scott Fujimoto, Herke van Hoof, David Meger
Addressing Function Approximation Error in Actor-Critic Methods. CoRR (2018)
Edward J. Smith, Scott Fujimoto, David Meger
3D Object Super-Resolution. CoRR (2018)
Scott Fujimoto, Herke van Hoof, David Meger
Addressing Function Approximation Error in Actor-Critic Methods. ICML (2018)