Kyle Gorman

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 3 papers; trusts 33 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 48 citations into it; #24,301 of 35,345 by trust here, #21,878 by citations
• Natural Language Processing — 43 citations into it
• Computer Vision and Pattern Recognition — 19 citations into it
• Model Architectures — 13 citations into it
• Speech & Audio — 10 citations into it
• Evaluation & Benchmarks — 5 citations into it; #2,187 of 3,147 by trust here, #2,704 by citations

Whom Kyle Gorman trusts overall

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

1. Christopher D. Manning
2. Michael Collins
3. Thorsten Brants
4. Diederik P. Kingma
5. Laurence S. Gillick
6. Jesús Giménez
7. Ron Artstein
8. David Yarowsky
9. Geoffrey E. Hinton
10. Mike Schuster

Who trusts Kyle Gorman overall

1. Anders Søgaard
2. Xiang Yu
3. Sebastian Ebert
4. Sayash Kapoor
5. Sebastian Gehrmann
6. Ngoc Thang Vu
7. Jasmijn Bastings

Papers from Kyle Gorman's perspective

Ordered by how strongly the researchers Kyle Gorman trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Attention is All you Need (Neural Information Processing Systems)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. ImageNet classification with deep convolutional neural networks
6. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• We Need to Talk about Standard Splits (2019) — 130 citations
• The SIGMORPHON 2020 Shared Task on Multilingual Grapheme-to-Phoneme Conversion (2020) — 56 citations
• Neural Models of Text Normalization for Speech Applications (2019) — 98 citations