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Jonathan Scholz — most-cited papers & profile · Reinforcement Learning
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Jonathan Scholz
6
papers ·
632
citations
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Semantic Scholar ↗
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Most-cited papers
Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards
2017 · 510 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
Mel Vecerik
· 3
David Barker
· 2
Oleg Sushkov
· 2
Thomas Roth\"orl
· 2
Alexander Novikov
· 1
Bilal Piot
· 1
Christopher Schuster
· 1
David Budden
· 1
Fumin Wang
· 1
Heni Ben Amor
· 1
Jean-Baptiste Regli
· 1
Kevin Sebastian Luck
· 1
Topics
Policy Gradient
Offline RL
Exploration
Model-Based RL
Safe RL
Value-Based