Matthew R. Gormley

Artificial Intelligence · 2012–2019

A researcher in the Science corpus: 5 papers; trusts 83 researchers and is trusted by 60 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 66 citations into it; #15,629 of 35,345 by trust here, #16,471 by citations
• Natural Language Processing — 39 citations into it; #1,066 of 5,688 by trust here, #2,333 by citations
• Computer Vision and Pattern Recognition — 18 citations into it
• Optimization & Training — 17 citations into it
• Management Science and Operations Research — 11 citations into it
• Model Architectures — 9 citations into it
• Computational Theory and Mathematics — 8 citations into it
• Evaluation & Benchmarks — 8 citations into it; #520 of 3,147 by trust here, #1,467 by citations

Whom Matthew R. Gormley trusts overall

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

1. Jason Eisner
2. Richard Socher
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Christopher D. Manning
6. Ilya Sutskever
7. Martin J. Wainwright
8. Veselin Stoyanov
9. Tomas Mikolov
10. Alex Graves

Who trusts Matthew R. Gormley overall

1. Xu Han
2. Tianyu Gao
3. Thien Huu Nguyen
4. Yiheng Liu
5. Ellie Pavlick
6. Lei Yu
7. Zhiyuan Liu
8. Alexander M. Rush
9. Alexios Gidiotis
10. Graham Neubig

Papers from Matthew R. Gormley's perspective

Ordered by how strongly the researchers Matthew R. Gormley 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. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Approximation-Aware Dependency Parsing by Belief Propagation (2015) — 36 citations
• Learning Beam Search Policies via Imitation Learning (2018) — 28 citations
• Improved Relation Extraction with Feature-Rich Compositional Embedding Models (2015) — 181 citations
• Towards modular and programmable architecture search (2019) — 31 citations
• Annotated Gigaword (2012) — 376 citations