Jason Lee

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 5 papers; trusts 368 researchers and is trusted by 123 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it; #2,214 of 35,345 by trust here, #5,458 by citations
• Computer Vision and Pattern Recognition — 73 citations into it; #3,263 of 21,575 by trust here, #4,067 by citations
• Natural Language Processing — 61 citations into it; #664 of 5,688 by trust here, #1,316 by citations
• Model Architectures — 24 citations into it
• Multimodal Learning — 14 citations into it
• Evaluation & Benchmarks — 10 citations into it
• Reinforcement Learning — 8 citations into it
• Generative Models — 7 citations into it

Whom Jason Lee trusts overall

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

1. Diederik P. Kingma
2. Kyunghyun Cho
3. Yoshua Bengio
4. Ilya Sutskever
5. Geoffrey E. Hinton
6. Dzmitry Bahdanau
7. Kaiming He
8. Alex Krizhevsky
9. Yann LeCun
10. Jimmy Ba

Who trusts Jason Lee overall

1. Jiatao Gu
2. Yonatan Belinkov
3. Kyunghyun Cho
4. William Chan
5. Rico Sennrich
6. Yichen Gong
7. Jungo Kasai
8. Marjan Ghazvininejad
9. Yaniv Taigman
10. Graham Neubig

Papers from Jason Lee's perspective

Ordered by how strongly the researchers Jason Lee 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. Long Short-Term Memory
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement (2018) — 498 citations
• Fully Character-Level Neural Machine Translation without Explicit Segmentation (2016) — 469 citations
• Emergent Translation in Multi-Agent Communication (2017) — 69 citations
• Optimization for drone and drone-truck combined operations: A review of the state of the art and future directions (2020) — 362 citations
• Responses of pink salmon to CO2-induced aquatic acidification (2015) — 212 citations