Kyle Hsu

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kyle Hsu trusts overall

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

  1. J. Urgen Schmidhuber
  2. Geoffrey E. Hinton
  3. Sergey Levine
  4. Diederik P. Kingma
  5. Kaiming He
  6. Chelsea Finn
  7. Yoshua Bengio
  8. Alex Krizhevsky
  9. Pieter Abbeel
  10. Richard S. Sutton

Papers from Kyle Hsu's perspective

Ordered by how strongly the researchers Kyle Hsu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Auto-Encoding Variational Bayes (International Conference on Learning Representations)

Their papers