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Mark Rowland — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Mark Rowland
21
papers ·
347
citations ·
20
h-index
Google DeepMind (United Kingdom) · Google (United Kingdom)
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Semantic Scholar ↗
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Most-cited papers
Distributional Reinforcement Learning with Quantile Regression
2017 · 150 citations
Revisiting Fundamentals of Experience Replay
2020 · 83 citations
An Analysis of Categorical Distributional Reinforcement Learning
2018 · 43 citations
Statistics and Samples in Distributional Reinforcement Learning
2019 · 24 citations
MICo: Improved representations via sampling-based state similarity for Markov decision processes
2021 · 22 citations
A General Theoretical Paradigm to Understand Learning from Human Preferences
2023 · 14 citations
Adaptive Trade-Offs in Off-Policy Learning
2019 · 5 citations
On The Effect of Auxiliary Tasks on Representation Dynamics
2021 · 2 citations
Revisiting Peng's Q($λ$) for Modern Reinforcement Learning
2021 · 1 citations
Unifying Gradient Estimators for Meta-Reinforcement Learning via Off-Policy Evaluation
2021 · 1 citations
Nash Learning from Human Feedback
2023 · 1 citations
Distributional Bellman Operators over Mean Embeddings
2023 · 1 citations
Optimizing Return Distributions with Distributional Dynamic Programming
2025
Conditional Importance Sampling for Off-Policy Learning
2019
Taylor Expansion of Discount Factors
2021
Top co-authors
R\'emi Munos
· 15
Will Dabney
· 12
Yunhao Tang
· 10
Michal Valko
· 8
Marc G. Bellemare
· 4
Clare Lyle
· 3
Tadashi Kozuno
· 3
Anna Harutyunyan
· 2
Bernardo \'Avila Pires
· 2
Bilal Piot
· 2
Daniele Calandriello
· 2
David Abel
· 2
Topics
Value-Based
Policy Gradient
Game AI
Offline RL
Exploration
Model-Based RL
Safe RL
Meta-RL
RLHF & Alignment
Multi-Agent