Dennis Lee

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 4 papers; trusts 57 researchers and is trusted by 17 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 71 citations into it; #9,960 of 35,345 by trust here, #7,241 by citations
• Reinforcement Learning — 54 citations into it; #1,340 of 2,242 by trust here, #895 by citations
• Computer Vision and Pattern Recognition — 29 citations into it
• Control and Systems Engineering — 27 citations into it; #3,690 of 8,257 by trust here, #906 by citations
• Large Language Models — 19 citations into it
• Natural Language Processing — 19 citations into it
• Optimization & Training — 12 citations into it
• Computational Theory and Mathematics — 8 citations into it

Whom Dennis Lee trusts overall

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

1. John Schulman
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Ilya Sutskever
5. Richard S. Sutton
6. Guillaume Lample
7. Yoshua Bengio
8. Pieter Abbeel
9. Sergey Levine
10. Alex Krizhevsky

Who trusts Dennis Lee overall

1. Chelsea Finn
2. Annie Xie
3. Sae-Young Chung
4. Yuhuai Wu
5. Tianhe Yu
6. Ron Dorfman
7. Sergey Levine
8. Ajay Mandlekar
9. Corey Lynch
10. James Harrison

Papers from Dennis Lee's perspective

Ordered by how strongly the researchers Dennis Lee 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. 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Deep Imitation Learning for Complex Manipulation Tasks from Virtual Reality Teleoperation (2017) — 778 citations
• ProMP: Proximal Meta-Policy Search (2018) — 227 citations
• Mathematical Reasoning via Self-supervised Skip-tree Training (2020) — 65 citations
• Language Modeling for Formal Mathematics (2020)