Alexander Lacoste

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Alexander Lacoste trusts

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

  1. Diederik P. Kingma (in Artificial Intelligence)
  2. Jimmy Ba (in Artificial Intelligence)
  3. Sergey Levine (in Artificial Intelligence)
  4. Yoshua Bengio (in Artificial Intelligence)
  5. Marc'Aurelio Ranzato (in Computer Vision and Pattern Recognition)
  6. Geoffrey E. Hinton (in Artificial Intelligence)

Papers from Alexander Lacoste's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Gradient-based learning applied to document recognition
  6. Matching Networks for One Shot Learning
  7. Learning Multiple Layers of Features from Tiny Images
  8. Prototypical Networks for Few-shot Learning
  9. ImageNet: A large-scale hierarchical image database
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers