Scott Emmons

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 37 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it
• Reinforcement Learning — 30 citations into it
• Control and Systems Engineering — 8 citations into it

Whom Scott Emmons trusts overall

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

1. Sergey Levine
2. Scott Fujimoto
3. Geoffrey E. Hinton
4. Richard S. Sutton
5. John Schulman
6. Diederik P. Kingma
7. Pieter Abbeel
8. Aviral Kumar
9. Justin Fu
10. Yoshua Bengio

Who trusts Scott Emmons overall

1. Rafael Figueiredo Prudencio
2. Benjamin Eysenbach
3. Anurag Ajay
4. Guan Wang
5. Marcos Ricardo Omena de Albuquerque Máximo
6. Tianjun Zhang
7. Yilun Du

Papers from Scott Emmons's perspective

Ordered by how strongly the researchers Scott Emmons 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• RvS: What is Essential for Offline RL via Supervised Learning? (2021) — 241 citations