Raúl Ramos-Pollán

Computer Vision and Pattern Recognition · 2016–2019

A researcher in the Science corpus: 5 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Raúl Ramos-Pollán trusts overall

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

  1. Yoshua Bengio
  2. Alex Krizhevsky
  3. Yann LeCun
  4. Geoffrey E. Hinton

Papers from Raúl Ramos-Pollán's perspective

Ordered by how strongly the researchers Raúl Ramos-Pollán trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers