Ying Jin

Artificial Intelligence · with Burlacu · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 51 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Ying Jin trusts overall

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

  1. Csaba Szepesvari
  2. Richard S. Sutton
  3. R´emi Munos
  4. J. Urgen Schmidhuber
  5. Aviral Kumar
  6. Andrew Barto
  7. Hui Zou
  8. Geoffrey E. Hinton
  9. Sergey Levine
  10. David L. Donoho

Who trusts Ying Jin overall

  1. Masatoshi Uehara
  2. Rasool Fakoor
  3. Paria Rashidinejad
  4. Tengyang Xie
  5. Banghua Zhu
  6. Xuezhou Zhang
  7. Michael Janner
  8. Jonas W. Mueller
  9. Ching-An Cheng
  10. Jiantao Jiao

Papers from Ying Jin's perspective

Ordered by how strongly the researchers Ying Jin 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. ImageNet: A large-scale hierarchical image database
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Long Short-Term Memory
  8. Reinforcement Learning: An Introduction
  9. Human-level control through deep reinforcement learning
  10. Learning Multiple Layers of Features from Tiny Images

Their papers