David S. Kung

Artificial Intelligence · 2019–2021

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

Subfields

Whom David S. Kung trusts overall

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

  1. Miltiadis Allamanis
  2. Alex Krizhevsky
  3. Kaiming He
  4. Geoffrey E. Hinton
  5. Tal Ben-Nun
  6. Sifei Luan
  7. Yoshua Bengio
  8. Diederik P. Kingma
  9. Thomas Kipf
  10. Ilya Sutskever

Papers from David S. Kung's perspective

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

Their papers