Suma Bhat

Natural Language Processing · 2017–2021

A researcher in the Science corpus: 3 papers; trusts 163 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Natural Language Processing — 83 citations into it; #2,142 of 5,688 by trust here, #3,421 by citations
• Artificial Intelligence — 71 citations into it; #11,435 of 35,345 by trust here, #16,166 by citations
• Representation & Self-Supervised Learning — 30 citations into it; #1,341 of 3,145 by trust here, #1,982 by citations
• Evaluation & Benchmarks — 20 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it; #17,222 of 21,575 by trust here, #20,271 by citations
• Model Architectures — 12 citations into it

Whom Suma Bhat trusts overall

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

1. Richard Socher
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Eneko Agirre
5. Tomas Mikolov
6. Ilya Sutskever
7. Diederik P. Kingma
8. Sepp Hochreiter
9. Alex Krizhevsky
10. Christopher D. Manning

Who trusts Suma Bhat overall

1. João Sedoc
2. Nina Poerner
3. William Timkey
4. Lyle Ungar
5. Alireza Salemi
6. Tianlin Liu
7. Dilin Wang
8. Benjamin Robaidek
9. Fangyu Liu
10. Nikunj Saunshi

Papers from Suma Bhat's perspective

Ordered by how strongly the researchers Suma Bhat 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. Attention is All you Need (Neural Information Processing Systems)
4. Long Short-Term Memory
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• All-but-the-Top: Simple and Effective Postprocessing for Word Representations (2017) — 407 citations
• Representing Sentences as Low-Rank Subspaces (2017) — 27 citations
• Paraphrase Generation: A Survey of the State of the Art (2021) — 92 citations