Ye Jiang

Artificial Intelligence · 2019

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 Ye Jiang trusts overall

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

  1. Sergey Ioffe
  2. Felix Alexander Gers
  3. Christian Szegedy
  4. J. Urgen Schmidhuber
  5. Matthew E. Peters
  6. Yoon Kim
  7. Geoffrey E. Hinton
  8. Yoshua Bengio
  9. Tomas Mikolov
  10. Yann LeCun

Papers from Ye Jiang's perspective

Ordered by how strongly the researchers Ye Jiang 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. Attention is All you Need (Neural Information Processing Systems)
  4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  5. Long Short-Term Memory
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. ImageNet: A large-scale hierarchical image database
  9. GloVe: Global Vectors for Word Representation
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers