Alexander LeClair

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 68 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it; #18,384 of 35,345 by trust here, #23,731 by citations
• Natural Language Processing — 33 citations into it; #4,670 of 5,688 by trust here, #4,879 by citations
• Information Systems — 30 citations into it; #3,743 of 8,771 by trust here, #5,303 by citations
• Computer Vision and Pattern Recognition — 13 citations into it
• Code Generation & Program Synthesis — 9 citations into it; #161 of 220 by trust here, #185 by citations
• Software — 8 citations into it; #929 of 1,227 by trust here, #870 by citations
• Evaluation & Benchmarks — 7 citations into it
• Model Architectures — 6 citations into it

Whom Alexander LeClair trusts overall

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

1. Ilya Sutskever
2. Dzmitry Bahdanau
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Miltiadis Allamanis
6. Xing Hu
7. Oriol Vinyals
8. Kyunghyun Cho
9. Chin-Yew Lin
10. Diederik P. Kingma

Who trusts Alexander LeClair overall

1. Wasi Uddin Ahmad
2. Toufique Ahmed
3. Saikat Chakraborty
4. Jian Zhang
5. Prem Devanbu
6. Yanlin Wang
7. Zimin Chen
8. Baishakhi Ray
9. Sakib Haque
10. Kai-Wei Chang

Papers from Alexander LeClair's perspective

Ordered by how strongly the researchers Alexander LeClair 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• Improved Code Summarization via a Graph Neural Network (2020) — 335 citations
• A Neural Model for Generating Natural Language Summaries of Program Subroutines (2019) — 335 citations