PengWei Wang

Artificial Intelligence · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom PengWei Wang trusts

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

  1. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  2. Kaiming He (in Computer Vision and Pattern Recognition)
  3. Diederik P. Kingma (in Artificial Intelligence)
  4. Karen Simonyan (in Computer Vision and Pattern Recognition)

Papers from PengWei Wang's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  3. Dropout: a simple way to prevent neural networks from overfitting
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. ImageNet classification with deep convolutional neural networks
  6. A Simple Framework for Contrastive Learning of Visual Representations (International Conference on Machine Learning)
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Gradient-based learning applied to document recognition
  9. Long Short-Term Memory
  10. ImageNet: A large-scale hierarchical image database

Their papers