Yajun Chen

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Yajun Chen trusts overall

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

  1. Paul Bergmann
  2. Niv Cohen
  3. Zhaowei Cai
  4. Adamu Ali-Gombe
  5. Thomas Schlegl
  6. Samet Akcay
  7. Thomas Defard
  8. Tal Reiss
  9. Yedid Hoshen
  10. Michael Fauser

Papers from Yajun Chen's perspective

Ordered by how strongly the researchers Yajun Chen 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. Learning Multiple Layers of Features from Tiny Images
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. ImageNet Large Scale Visual Recognition Challenge
  7. GENERATIVE ADVERSARIAL NETS
  8. Going deeper with convolutions
  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