Hai Tan

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Hai Tan trusts overall

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

  1. Geoffrey E. Hinton
  2. Paul J. Werbos
  3. Alex Graves
  4. Yoshua Bengio
  5. J. Urgen Schmidhuber
  6. Yann LeCun
  7. Alex Krizhevsky
  8. Ilya Sutskever
  9. David E. Rumelhart
  10. L. Eon Bottou

Papers from Hai Tan's perspective

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

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

Their papers