Emmanuel Rachelson

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Reinforcement Learning — 12 citations into it
• Management Science and Operations Research — 6 citations into it

Whom Emmanuel Rachelson trusts overall

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

1. Richard S. Sutton
2. Cédric Villani
3. Martin A. Dufwenberg
4. Ryuichi Oka
5. Jason Pazis
6. Andrew Barto
7. Robert D. Kleinberg
8. Daniel L. Silver
9. Matteo Pirotta
10. Emmanuel Hadoux

Who trusts Emmanuel Rachelson overall

1. Christian Alexander Steinparz

Papers from Emmanuel Rachelson's perspective

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

1. Reinforcement Learning: An Introduction
2. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
3. Markov Decision Processes: Discrete Stochastic Dynamic Programming
4. Mastering the game of Go with deep neural networks and tree search
5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
6. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
7. ImageNet classification with deep convolutional neural networks
8. Gradient-based learning applied to document recognition
9. Planning and Acting in Partially Observable Stochastic Domains
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Non-Stationary Markov Decision Processes a Worst-Case Approach using Model-Based Reinforcement Learning (2019) — 100 citations