Steven Kapturowski

Reinforcement Learning · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 40 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 116 citations into it; #1,602 of 2,242 by trust here, #992 by citations
• Artificial Intelligence — 111 citations into it
• Cognitive Neuroscience — 15 citations into it
• Optimization & Training — 9 citations into it
• Electrical and Electronic Engineering — 7 citations into it

Whom Steven Kapturowski trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Richard S. Sutton
2. Paul J. Werbos
3. Volodymyr Mnih
4. Longxin Lin
5. Marc G. Bellemare
6. Tom Schaul
7. Andrew Barto
8. J. Urgen Schmidhuber
9. Matteo Hessel
10. Sepp Hochreiter

Who trusts Steven Kapturowski overall

1. Hengyuan Hu
2. Danijar Hafner
3. Adrià Puigdomènech Badia
4. Annie Xie
5. Pieter Abbeel
6. Adam Stooke
7. Caglar Gulcehre
8. Timothy P. Lillicrap
9. Joshua Achiam
10. Nino Vieillard

Papers from Steven Kapturowski's perspective

Ordered by how strongly the researchers Steven Kapturowski trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Reinforcement Learning: An Introduction
8. ImageNet: A large-scale hierarchical image database
9. Asynchronous Methods for Deep Reinforcement Learning
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Agent57: Outperforming the Atari Human Benchmark (2020) — 594 citations
• Never Give Up: Learning Directed Exploration Strategies (2020) — 360 citations
• Making Efficient Use of Demonstrations to Solve Hard Exploration Problems (2019) — 97 citations
• Recurrent Experience Replay in Distributed Reinforcement Learning (2018) — 568 citations