Tao Fan

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 8 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Tao Fan trusts overall

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

  1. Cynthia Dwork
  2. H. Brendan McMahan
  3. Yang Liu
  4. Pascal Paillier
  5. Jakub Konecný
  6. Jorge Nocedal
  7. Reza Shokri
  8. Tianqi Chen
  9. Gang Liang
  10. Geoffrey E. Hinton

Who trusts Tao Fan overall

  1. Yang Liu
  2. Xuefei Yin
  3. Haokun Fang
  4. Qinbin Li
  5. Yanming Zhu
  6. Hangyu Zhu

Papers from Tao Fan's perspective

Ordered by how strongly the researchers Tao Fan 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. Gradient-based learning applied to document recognition
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Learning Multiple Layers of Features from Tiny Images
  6. Long Short-Term Memory
  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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers