Rousslan Fernand Julien Dossa

Reinforcement Learning · 2022

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 17 citations into it
• Artificial Intelligence — 13 citations into it

Whom Rousslan Fernand Julien Dossa trusts overall

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

1. E. Todorov
2. John Schulman
3. Shengyi Huang
4. Marc G. Bellemare
5. Volodymyr Mnih
6. Scott Fujimoto
7. Timothy P. Lillicrap

Papers from Rousslan Fernand Julien Dossa's perspective

Ordered by how strongly the researchers Rousslan Fernand Julien Dossa trusts endorse each paper. Same corpus, a different order for every researcher.

1. Proximal Policy Optimization Algorithms (arXiv.org)
2. Playing Atari with Deep Reinforcement Learning (arXiv.org)
3. MuJoCo: A physics engine for model-based control
4. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
5. The Arcade Learning Environment: An Evaluation Platform for General Agents
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. ImageNet classification with deep convolutional neural networks
8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
9. Gradient-based learning applied to document recognition
10. Asynchronous Methods for Deep Reinforcement Learning

Their papers

• CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms (2022) — 510 citations