Ben Day

Molecular Biology · 2021

A researcher in the Science corpus: 2 papers; trusts 7 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Molecular Biology — 72 citations into it
• Artificial Intelligence — 57 citations into it
• Computational Theory and Mathematics — 51 citations into it
• Graph Learning — 42 citations into it
• Computational Chemistry & Drug Discovery — 19 citations into it
• Generative Models — 9 citations into it
• Pharmacology — 9 citations into it

Whom Ben Day trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Thomas Kipf
5. Max Welling
6. Yann LeCun
7. Alex Krizhevsky
8. Tomas Mikolov
9. Petar Velickovic
10. Ilya Sutskever

Papers from Ben Day's perspective

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

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Utilizing graph machine learning within drug discovery and development (2021) — 308 citations
• Structure-aware generation of drug-like molecules (2021) — 21 citations