Marco Re

Reinforcement Learning · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 34 citations into it
• Artificial Intelligence — 29 citations into it

Whom Marco Re trusts overall

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

1. Richard S. Sutton

Papers from Marco Re's perspective

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

1. Reinforcement Learning: An Introduction
2. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
3. Asynchronous Methods for Deep Reinforcement Learning
4. Human-level control through deep reinforcement learning
5. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
6. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
7. Trust Region Policy Optimization (International Conference on Machine Learning)
8. Curriculum learning
9. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
10. ImageNet classification with deep convolutional neural networks

Their papers

• Multi-Agent Reinforcement Learning: A Review of Challenges and Applications (2021) — 426 citations