Daniel Huang

Artificial Intelligence · 2014–2023

A researcher in the Science corpus: 3 papers; trusts 14 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Daniel Huang trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Alex Krizhevsky
  4. Richard Socher
  5. Yoshua Bengio
  6. Jimmy Ba
  7. Christian Szegedy
  8. Ilya Sutskever
  9. Corinna Cortes
  10. Nitish Srivastava

Who trusts Daniel Huang overall

  1. Markus Norman Rabe
  2. Yuhuai Wu
  3. Stanislas Polu
  4. Kshitij Bansal
  5. Kaiyu Yang
  6. Xinyun Chen
  7. Wenda Li
  8. Christian Szegedy
  9. Sean Welleck
  10. Emily First

Papers from Daniel Huang's perspective

Ordered by how strongly the researchers Daniel Huang 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Going deeper with convolutions

Their papers