Sangkug Lym

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 2 papers; trusts 43 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Sangkug Lym trusts overall

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

  1. Kaiming He
  2. Alex Krizhevsky
  3. Geoffrey E. Hinton
  4. Sergey Ioffe
  5. Ross B. Girshick
  6. Karen Simonyan
  7. José Manuel Álvarez
  8. Song Han
  9. Ilya Sutskever
  10. X. Zhang

Who trusts Sangkug Lym overall

  1. Yuang Jiang

Papers from Sangkug Lym's perspective

Ordered by how strongly the researchers Sangkug Lym 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. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Going deeper with convolutions

Their papers