Jin-Hyuk Hong

Natural Language Processing · 2018

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Jin-Hyuk Hong trusts overall

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

  1. Qian Chen
  2. Tomas Mikolov
  3. Kaiming He
  4. Alex Graves
  5. Geoffrey E. Hinton
  6. Yoshua Bengio
  7. Ilya Sutskever
  8. Diederik P. Kingma
  9. Richard Socher
  10. Alex Krizhevsky

Who trusts Jin-Hyuk Hong overall

  1. Zhiquan Ye
  2. Shervin Minaee
  3. Shane Storks
  4. Bryan McCann
  5. Haoyu Song

Papers from Jin-Hyuk Hong's perspective

Ordered by how strongly the researchers Jin-Hyuk Hong 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. Attention is All you Need (Neural Information Processing Systems)
  3. ImageNet classification with deep convolutional neural networks
  4. Long Short-Term Memory
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers