Song Bian

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Song Bian trusts overall

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

  1. Kaspar Riesen
  2. Horst Bunke
  3. Diederik P. Kingma
  4. William L. Hamilton
  5. Geoffrey E. Hinton
  6. Richard Socher

Papers from Song Bian's perspective

Ordered by how strongly the researchers Song Bian 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. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Long Short-Term Memory
  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. ImageNet: A large-scale hierarchical image database
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers