Feijun Jiang

Artificial Intelligence · 2022

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Feijun Jiang 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 Feijun Jiang's perspective

Ordered by how strongly the researchers Feijun Jiang 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. A Simple Framework for Contrastive Learning of Visual Representations (International Conference on Machine Learning)
  5. Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning
  6. PyTorch: An Imperative Style, High-Performance Deep Learning Library
  7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  8. Signature Verification Using A "Siamese" Time Delay Neural Network
  9. ImageNet classification with deep convolutional neural networks
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers