Ya Tu

Artificial Intelligence · 2020

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 Ya Tu trusts overall

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

  1. Tim O'Shea
  2. Alex Krizhevsky
  3. Augustus Odena
  4. Geoffrey E. Hinton

Papers from Ya Tu's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Long Short-Term Memory
  6. Going deeper with convolutions
  7. Learning Multiple Layers of Features from Tiny Images
  8. One-shot learning of object categories
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers