Jun Chin Ang

Molecular Biology · 2016

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 Jun Chin Ang trusts overall

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

  1. David E. Goldberg
  2. Chris H. Q. Ding
  3. Feiping Nie
  4. Daniela M. Witten
  5. Piyushkumar A. Mundra
  6. Anil K. Jain
  7. Christos Boutsidis
  8. Cathy Maugis
  9. Roy Varshavsky
  10. Ali Anaissi

Papers from Jun Chin Ang's perspective

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

Their papers