Seunghak Yu

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 6 papers; trusts 432 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Seunghak Yu trusts overall

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

  1. Geoffrey E. Hinton
  2. Yoshua Bengio
  3. Ilya Sutskever
  4. Alex Graves
  5. Alex Krizhevsky
  6. Diederik P. Kingma
  7. Kaiming He
  8. Matthew D. Zeiler
  9. Oriol Vinyals
  10. Yann LeCun

Who trusts Seunghak Yu overall

  1. Mark Anderson
  2. Giovanni Da San Martino
  3. Raphael Tang
  4. Andrew Straiton Hard
  5. Carlos Gómez-Rodríguez
  6. Alberto Barrón-Cedeño
  7. Preslav Nakov
  8. Xiuyi Chen
  9. Van-Quang Nguyen
  10. Kung-Hsiang Huang

Papers from Seunghak Yu's perspective

Ordered by how strongly the researchers Seunghak Yu 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. Long Short-Term Memory
  5. Attention is All you Need (Neural Information Processing Systems)
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  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