Richard Ryan Williams

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 2 papers; trusts 130 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 28 citations into it
• Reinforcement Learning — 18 citations into it
• Computational Theory and Mathematics — 11 citations into it; #4,070 of 12,182 by trust here, #11,462 by citations
• Algorithms & Complexity — 7 citations into it
• Natural Language Processing — 5 citations into it

Whom Richard Ryan Williams trusts overall

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

1. Jacob Andreas
2. Richard S. Sutton
3. Geoffrey E. Hinton
4. Drew A. Hudson
5. Jakob N. Foerster
6. Sainbayar Sukhbaatar
7. Yoshua Bengio
8. Diederik P. Kingma
9. Marcus Rohrbach
10. Scott Fujimoto

Who trusts Richard Ryan Williams overall

1. Henry Corrigan-Gibbs
2. Dan Boneh
3. Elette Boyle
4. Afshin Oroojlooyjadid
5. Filippos Christianos
6. Niv Gilboa

Papers from Richard Ryan Williams's perspective

Ordered by how strongly the researchers Richard Ryan Williams 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Strong ETH Breaks With Merlin and Arthur: Short Non-Interactive Proofs of Batch Evaluation (2016) — 65 citations
• Learning Multi-Agent Communication through Structured Attentive Reasoning (2020) — 41 citations