Lauv Patel

Computational Theory and Mathematics · 2020

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 26 citations into it
• Molecular Biology — 22 citations into it
• Materials Chemistry — 10 citations into it
• Computational Chemistry & Drug Discovery — 5 citations into it

Whom Lauv Patel trusts overall

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

1. Marwin H. S. Segler
2. Corinna Cortes
3. Mark P. Waller
4. Jamil Fayyad
5. Matthew Ragoza
6. H. C. Stephen Chan
7. Vladimir Naumovich Vapnik
8. Sean Ekins
9. Peter D. Chang
10. Geoffrey E. Hinton

Papers from Lauv Patel's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Dropout: a simple way to prevent neural networks from overfitting
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. ImageNet Large Scale Visual Recognition Challenge
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Going deeper with convolutions

Their papers

• Machine Learning Methods in Drug Discovery (2020) — 324 citations