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Mel Vecerik — most-cited papers & profile · Reinforcement Learning
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Mel Vecerik
14
papers ·
954
citations
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
2017 · 510 citations
Sim-to-Real Robot Learning from Pixels with Progressive Nets
2016 · 109 citations
Robust Multi-Modal Policies for Industrial Assembly via Reinforcement Learning and Demonstrations: A Large-Scale Study
2021 · 87 citations
Scaling data-driven robotics with reward sketching and batch reinforcement learning
2019 · 45 citations
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency
2020 · 14 citations
Improved Exploration through Latent Trajectory Optimization in Deep Deterministic Policy Gradient
2019 · 4 citations
Top co-authors
Jonathan Scholz
· 4
Oleg Sushkov
· 3
Thomas Roth\"orl
· 3
David Barker
· 2
Nicolas Heess
· 2
Raia Hadsell
· 2
Rugile Pevceviciute
· 2
Alexander Novikov
· 1
Andrei A. Rusu
· 1
Bilal Piot
· 1
Chang Su
· 1
Christopher Schuster
· 1
Topics
Policy Gradient
Model-Based RL
Value-Based
Offline RL
Exploration
Safe RL
Meta-RL
Multi-Agent