Ching-An Cheng

Artificial Intelligence · with Boots · 2016–2019

A researcher in the Science corpus: 9 papers; trusts 193 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

Whom Ching-An Cheng trusts overall

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

  1. Sham M. Kakade
  2. Richard S. Sutton
  3. Stéphane Ross
  4. Geoffrey E. Hinton
  5. Elad Hazan
  6. Ronald J. Williams
  7. Diederik P. Kingma
  8. Jan Peters
  9. Shun-ichi Amari
  10. John Schulman

Who trusts Ching-An Cheng overall

  1. Sergey Levine
  2. Jiawei Huang
  3. Xinyan Yan
  4. Tim G. J. Rudner
  5. Byron Boots
  6. Nan Jiang
  7. Chelsea Finn
  8. Xuanyi Dong
  9. Aravind Rajeswaran
  10. Liyiming Ke

Papers from Ching-An Cheng's perspective

Ordered by how strongly the researchers Ching-An Cheng 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. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers