Nathaniel Thomas

Molecular Biology · with Dror · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 5 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 28 citations into it
• Materials Chemistry — 27 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it; #9,390 of 21,575 by trust here, #6,281 by citations
• Computational Chemistry & Drug Discovery — 13 citations into it
• Model Architectures — 12 citations into it; #1,057 of 2,278 by trust here, #860 by citations
• Artificial Intelligence — 10 citations into it

Whom Nathaniel Thomas trusts overall

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

1. Taco Cohen
2. Risi Kondor
3. Kristof T. Schütt
4. Charles Ruizhongtai Qi
5. Stefan Chmiela
6. Izhar Wallach
7. Max Welling
8. Daniel E. Worrall
9. R. Ramakrishnan
10. Zhirong Wu

Who trusts Nathaniel Thomas overall

1. Bowen Jing
2. David W. Romero
3. Raphael J. L. Townshend
4. Petar Velickovic
5. Octavian-Eugen Ganea
6. Risi Kondor
7. Stephan Eismann
8. Maurice Weiler
9. Hannes Stärk
10. Erik J. Bekkers

Papers from Nathaniel Thomas's perspective

Ordered by how strongly the researchers Nathaniel Thomas 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet: A large-scale hierarchical image database
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Long Short-Term Memory

Their papers

• Tensor Field Networks: Rotation- and Translation-Equivariant Neural Networks for 3D Point Clouds (2018) — 1,225 citations
• Hierarchical, rotation‐equivariant neural networks to select structural models of protein complexes (2020) — 68 citations