Seung-won Hwang

Artificial Intelligence · with Choi · 2021

A researcher in the Science corpus: 1 paper; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Seung-won Hwang trusts overall

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

  1. Diederik P. Kingma
  2. Andrew L. Maas
  3. Yoshua Bengio
  4. Kaiming He
  5. Anette Hulth
  6. Geoffrey E. Hinton

Papers from Seung-won Hwang's perspective

Ordered by how strongly the researchers Seung-won Hwang 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  4. ImageNet classification with deep convolutional neural networks
  5. Long Short-Term Memory
  6. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
  7. Gradient-based learning applied to document recognition
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet: A large-scale hierarchical image database
  10. Learning Multiple Layers of Features from Tiny Images

Their papers