Akash Velu

Reinforcement Learning · 2021

A researcher in the Science corpus: 2 papers; trusts 27 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 71 citations into it
• Artificial Intelligence — 56 citations into it
• LLM Agents & Tool Use — 7 citations into it
• Economics and Econometrics — 5 citations into it

Whom Akash Velu trusts overall

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

1. John Schulman
2. Jakob N. Foerster
3. Tabish Rashid
4. Pieter Abbeel
5. Richard S. Sutton
6. Hengyuan Hu
7. Geoffrey E. Hinton
8. Sergey Levine
9. Diederik P. Kingma
10. Georgios Papoudakis

Who trusts Akash Velu overall

1. Jakub Grudzien Kuba

Papers from Akash Velu's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Reinforcement Learning: An Introduction
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Human-level control through deep reinforcement learning

Their papers

• The Surprising Effectiveness of PPO in Cooperative Multi-Agent Games (2021) — 2,481 citations
• The Surprising Effectiveness of MAPPO in Cooperative, Multi-Agent Games (2021) — 208 citations