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Olivier Bachem — most-cited papers & profile · Reinforcement Learning
← authors
·
overview
Olivier Bachem
29
papers ·
607
citations ·
29
h-index
ETH Zurich
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
What Matters In On-Policy Reinforcement Learning? A Large-Scale Empirical Study
2020 · 105 citations
Brax -- A Differentiable Physics Engine for Large Scale Rigid Body Simulation
2021 · 62 citations
Concave Utility Reinforcement Learning: the Mean-Field Game Viewpoint
2021 · 9 citations
The Role of Pretrained Representations for the OOD Generalization of Reinforcement Learning Agents
2021 · 3 citations
A general class of surrogate functions for stable and efficient reinforcement learning
2021 · 3 citations
WARM: On the Benefits of Weight Averaged Reward Models
2024 · 3 citations
Braxlines: Fast and Interactive Toolkit for RL-driven Behavior Engineering beyond Reward Maximization
2021 · 1 citations
Nash Learning from Human Feedback
2023 · 1 citations
WARP: On the Benefits of Weight Averaged Rewarded Policies
2024 · 1 citations
Imitating Language via Scalable Inverse Reinforcement Learning
2024 · 1 citations
Google Research Football: A Novel Reinforcement Learning Environment
2019
Offline Reinforcement Learning as Anti-Exploration
2021
On the importance of data collection for training general goal-reaching policies
2022
Top co-authors
Matthieu Geist
· 7
L\'eonard Hussenot
· 5
Nino Vieillard
· 5
Sertan Girgin
· 5
Olivier Pietquin
· 4
Robert Dadashi
· 4
Alexandre Ram\'e
· 3
Johan Ferret
· 3
Nikola Momchev
· 3
Bilal Piot
· 2
Daniele Calandriello
· 2
Erik Frey
· 2
Topics
Policy Gradient
Exploration
Model-Based RL
Safe RL
RLHF & Alignment
Game AI
Value-Based
Multi-Agent
Offline RL
Meta-RL