Wei Huang

Artificial Intelligence · 3 papers · 2022–2023

A researcher in the Science corpus: 3 papers; trusts 79 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Wei Huang trusts overall

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

  1. Geoffrey E. Hinton
  2. Kaiming He
  3. Alex Krizhevsky
  4. Ronald J. Williams
  5. Yoshua Bengio
  6. Diederik P. Kingma
  7. Ilya Sutskever
  8. Ilya Loshchilov
  9. Yann LeCun
  10. Karen Simonyan

Papers from Wei Huang's perspective

Ordered by how strongly the researchers Wei 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. Attention is All you Need (Neural Information Processing Systems)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. ImageNet: A large-scale hierarchical image database
  6. Long Short-Term Memory
  7. Gradient-based learning applied to document recognition
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  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