Bee-Chung Chen

Artificial Intelligence · 2008–2016

A researcher in the Science corpus: 7 papers; trusts 37 researchers and is trusted by 74 researchers here, as inferred from the citation graph.

Subfields

Whom Bee-Chung Chen trusts overall

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

  1. Ruslan Salakhutdinov
  2. Yehuda Koren
  3. Eric R. Ziegel
  4. Radford M. Neal
  5. David M. Blei
  6. Andriy Mnih
  7. Arthur P. Dempster
  8. Robert M. Bell
  9. Geoffrey E. Hinton
  10. Joseph Hilbe

Who trusts Bee-Chung Chen overall

  1. Hao Wang
  2. Qingyun Wu
  3. Lihong Li
  4. Deepak K. Agarwal
  5. Wei Chu
  6. Shuang-Hong Yang
  7. Hang Li
  8. Yue Shi
  9. Chong Wang
  10. Hongning Wang

Papers from Bee-Chung Chen's perspective

Ordered by how strongly the researchers Bee-Chung Chen 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers