Patrick LaVictoire

Artificial Intelligence · 2014–2020

A researcher in the Science corpus: 3 papers; trusts 60 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

Whom Patrick LaVictoire trusts overall

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

  1. Moshe Tennenholtz
  2. Geoffrey E. Hinton
  3. Diederik P. Kingma
  4. Andrew Y. Ng
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Karen Simonyan
  8. Yann LeCun
  9. Alex Graves
  10. Ruslan Salakhutdinov

Who trusts Patrick LaVictoire overall

  1. Tom Everitt
  2. Andrew Critch
  3. Nick Bostrom

Papers from Patrick LaVictoire's perspective

Ordered by how strongly the researchers Patrick LaVictoire 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. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  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. Going deeper with convolutions

Their papers