J. Latorre

Computer Vision and Pattern Recognition · 2021

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

Whom J. Latorre trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Alex Krizhevsky
  4. Christian Szegedy
  5. Song Han
  6. Karen Simonyan
  7. Yoshua Bengio
  8. Diederik P. Kingma
  9. Joel Hestness
  10. Yann LeCun

Who trusts J. Latorre overall

  1. Elias Frantar

Papers from J. Latorre's perspective

Ordered by how strongly the researchers J. Latorre 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  4. Going deeper with convolutions
  5. ImageNet: A large-scale hierarchical image database
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Gradient-based learning applied to document recognition
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers