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ORCIDScott Fujimoto
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2020 – today
- 2024
[i13]Wenhao Zhan, Scott Fujimoto, Zheqing Zhu, Jason D. Lee, Daniel R. Jiang, Yonathan Efroni:
Exploiting Structure in Offline Multi-Agent RL: The Benefits of Low Interaction Rank. CoRR abs/2410.01101 (2024)- 2023
- [c10]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 - [i12]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 abs/2306.02451 (2023) - [i11]Wei-Di Chang, Scott Fujimoto, David Meger, Gregory Dudek:
Imitation Learning from Observation through Optimal Transport. CoRR abs/2310.01632 (2023) - 2022
- [c9]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: 6918-6943 - [i10]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 abs/2201.12417 (2022) - [i9]Wei-Di Chang, Juan Camilo Gamboa Higuera, Scott Fujimoto, David Meger, Gregory Dudek:
IL-flOw: Imitation Learning from Observation using Normalizing Flows. CoRR abs/2205.09251 (2022) - 2021
- [c8]Scott Fujimoto, David Meger, Doina Precup:
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation. ICML 2021: 3518-3529 - [c7]Scott Fujimoto, Shixiang Shane Gu:
A Minimalist Approach to Offline Reinforcement Learning. NeurIPS 2021: 20132-20145 - [i8]Scott Fujimoto, David Meger, Doina Precup:
A Deep Reinforcement Learning Approach to Marginalized Importance Sampling with the Successor Representation. CoRR abs/2106.06854 (2021) - [i7]Scott Fujimoto, Shixiang Shane Gu:
A Minimalist Approach to Offline Reinforcement Learning. CoRR abs/2106.06860 (2021) - 2020
- [c6]Scott Fujimoto, David Meger, Doina Precup:
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay. NeurIPS 2020 - [i6]Scott Fujimoto, David Meger, Doina Precup:
An Equivalence between Loss Functions and Non-Uniform Sampling in Experience Replay. CoRR abs/2007.06049 (2020)
2010 – 2019
- 2019
- [c5]Scott Fujimoto, David Meger, Doina Precup:
Off-Policy Deep Reinforcement Learning without Exploration. ICML 2019: 2052-2062 - [c4]Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger:
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. ICML 2019: 5866-5876 - [i5]Edward J. Smith, Scott Fujimoto, Adriana Romero, David Meger:
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects. CoRR abs/1901.11461 (2019) - [i4]Scott Fujimoto, Edoardo Conti, Mohammad Ghavamzadeh, Joelle Pineau:
Benchmarking Batch Deep Reinforcement Learning Algorithms. CoRR abs/1910.01708 (2019) - 2018
- [c3]Scott Fujimoto, Herke van Hoof, David Meger:
Addressing Function Approximation Error in Actor-Critic Methods. ICML 2018: 1582-1591 - [c2]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: 1886-1895 - [c1]Edward J. Smith, Scott Fujimoto, David Meger:
Multi-View Silhouette and Depth Decomposition for High Resolution 3D Object Representation. NeurIPS 2018: 6479-6489 - [i3]Scott Fujimoto, Herke van Hoof, David Meger:
Addressing Function Approximation Error in Actor-Critic Methods. CoRR abs/1802.09477 (2018) - [i2]Edward J. Smith, Scott Fujimoto, David Meger:
3D Object Super-Resolution. CoRR abs/1802.09987 (2018) - [i1]Scott Fujimoto, David Meger, Doina Precup:
Off-Policy Deep Reinforcement Learning without Exploration. CoRR abs/1812.02900 (2018)
Coauthor Index
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