Kevin McCloskey

Computational Theory and Mathematics · 2016

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Computational Theory and Mathematics — 23 citations into it; #2,790 of 12,182 by trust here, #434 by citations
• Molecular Biology — 19 citations into it
• Materials Chemistry — 14 citations into it; #1,674 of 11,513 by trust here, #3,109 by citations
• Computational Chemistry & Drug Discovery — 10 citations into it; #95 of 425 by trust here, #84 by citations

Whom Kevin McCloskey trusts overall

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

1. Jonathan Masci
2. Geoffrey E. Hinton
3. George E. Dahl
4. David E. Rumelhart
5. Andreas Mayr
6. Thomas Unterthiner
7. Ajay N. Jain
8. John C. Duchi
9. Anthony Nicholls
10. Alessandro Lusci

Who trusts Kevin McCloskey overall

1. Garrett B. Goh
2. Wengong Jin
3. Mukund Sundararajan
4. Kyle Swanson
5. Esben Jannik Bjerrum
6. Charles Siegel
7. Regina Barzilay
8. Diego Marcheggiani
9. Katsuhiko Ishiguro
10. Rex Ying

Papers from Kevin McCloskey's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Going deeper with convolutions
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization
10. Learning representations by back-propagating errors

Their papers

• Molecular graph convolutions: moving beyond fingerprints (2016) — 1,608 citations