Vivek Narayanan

Reinforcement Learning · 2018

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 — 26 citations into it
• Artificial Intelligence — 24 citations into it

Whom Vivek Narayanan trusts

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

1. Richard S. Sutton (in Reinforcement Learning)
2. Sergey Levine (in Artificial Intelligence)
3. Andrew Barto (in Reinforcement Learning)
4. Sargur N. Srihari (in Probabilistic & Bayesian Methods)
5. Lihong Li (in Reinforcement Learning)

Papers from Vivek Narayanan's perspective

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

1. Reinforcement Learning: An Introduction
2. Human-level control through deep reinforcement learning
3. Trust Region Policy Optimization (International Conference on Machine Learning)
4. Proximal Policy Optimization Algorithms (arXiv.org)
5. Deep Reinforcement Learning with Double Q-Learning
6. Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
7. Dueling Network Architectures for Deep Reinforcement Learning
8. PILCO: A Model-Based and Data-Efficient Approach to Policy Search
9. Rainbow: Combining Improvements in Deep Reinforcement Learning
10. OpenAI Gym

Their papers

• Horizon: Facebook's Open Source Applied Reinforcement Learning Platform (2018) — 147 citations