Neil Thomas

Molecular Biology · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 69 citations into it
• Computational Biology & Bioinformatics — 61 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it

Whom Neil Thomas trusts overall

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

1. Sean R. Eddy
2. Jacob Devlin
3. Burkhard Rost
4. Sepp Hochreiter
5. Stephen F. Altschul
6. Geoffrey E. Hinton
7. S. W. Lockless
8. Anthony Fodor
9. Tunca Dogan
10. Raymond C. Stevens

Who trusts Neil Thomas overall

1. Roshan Rao
2. Joshua Meier

Papers from Neil Thomas's perspective

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

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

Their papers

• Evaluating Protein Transfer Learning with TAPE (2019) — 1,047 citations
• Single Layers of Attention Suffice to Predict Protein Contacts (2020) — 35 citations