Bin Fu

Artificial Intelligence · with Wang · 2017

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Bin Fu trusts overall

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

  1. Diederik P. Kingma
  2. Sergey Ioffe
  3. Steffen Rendle
  4. Christian Szegedy
  5. Jimmy Ba

Who trusts Bin Fu overall

  1. Justin Engelmann
  2. Tongwen Huang
  3. Bin Liu
  4. Yu. V. Gorishniy
  5. Le Wu
  6. Pengyu Zhao
  7. Zilong Zhao

Papers from Bin Fu's perspective

Ordered by how strongly the researchers Bin Fu 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  4. ImageNet classification with deep convolutional neural networks
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Learning Multiple Layers of Features from Tiny Images
  8. Long Short-Term Memory
  9. Going deeper with convolutions
  10. ImageNet: A large-scale hierarchical image database

Their papers