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Anirudh Goyal โ most-cited papers & profile ยท Reinforcement Learning
โ authors
ยท
overview
Anirudh Goyal
30
papers ยท
477
citations ยท
25
h-index
Princeton University ยท University of Maryland, College Park
Google Scholar โ
Semantic Scholar โ
OpenAlex โ
Most-cited papers
An Actor-Critic Algorithm for Sequence Prediction
2016 ยท 224 citations
InfoBot: Transfer and Exploration via the Information Bottleneck
2019 ยท 47 citations
Recall Traces: Backtracking Models for Efficient Reinforcement Learning
2018 ยท 25 citations
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives
2019 ยท 23 citations
Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future
2019 ยท 17 citations
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget
2020 ยท 6 citations
Retrieval-Augmented Reinforcement Learning
2022 ยท 6 citations
Fast and Slow Learning of Recurrent Independent Mechanisms
2021 ยท 5 citations
Aligning Text-to-Image Diffusion Models with Reward Backpropagation
2023 ยท 5 citations
Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning
2021 ยท 4 citations
Discrete Factorial Representations as an Abstraction for Goal Conditioned Reinforcement Learning
2022 ยท 4 citations
Learning Powerful Policies by Using Consistent Dynamics Model
2019 ยท 3 citations
Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning
2019 ยท 2 citations
Stateful active facilitator: Coordination and Environmental Heterogeneity in Cooperative Multi-Agent Reinforcement Learning
2022 ยท 1 citations
Representation Learning in Deep RL via Discrete Information Bottleneck
2022 ยท 1 citations
Top co-authors
Yoshua Bengio
ยท 13
Sergey Levine
ยท 5
Aniket Didolkar
ยท 4
Nicolas Heess
ยท 4
Alex Lamb
ยท 3
Cristian Meo
ยท 3
Dianbo Liu
ยท 3
Vedant Shah
ยท 3
Hongyu Zang
ยท 2
Hugo Larochelle
ยท 2
Oussama Boussif
ยท 2
Shagun Sodhani
ยท 2
Topics
Model-Based RL
Exploration
Policy Gradient
Value-Based
Multi-Agent
Safe RL
Meta-RL
Offline RL
Game AI
cs.LG