Arrasy Rahman

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 56 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 63 citations into it; #19,882 of 35,345 by trust here, #20,836 by citations
• Reinforcement Learning — 56 citations into it
• Management Science and Operations Research — 15 citations into it
• Game & Decision Theory — 9 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• LLM Agents & Tool Use — 6 citations into it

Whom Arrasy Rahman trusts overall

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

1. Stefano V. Albrecht
2. Peter Stone
3. Richard S. Sutton
4. Volodymyr Mnih
5. Geoffrey E. Hinton
6. Sepp Hochreiter
7. Diederik P. Kingma
8. Samuel Barrett
9. Ronald J. Williams
10. J. Urgen Schmidhuber

Who trusts Arrasy Rahman overall

1. Georgios Papoudakis
2. Filippos Christianos
3. Stefano V. Albrecht
4. Lukas Schäfer

Papers from Arrasy Rahman's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. Human-level control through deep reinforcement learning
9. Reinforcement Learning: An Introduction
10. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Their papers

• Dealing with Non-Stationarity in Multi-Agent Deep Reinforcement Learning (2019) — 244 citations
• Scaling Multi-Agent Reinforcement Learning with Selective Parameter Sharing (2021) — 176 citations
• Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning (2020) — 79 citations