Sungwon Kim

Generative Models · with Yoon · 2018–2022

A researcher in the Science corpus: 5 papers; trusts 371 researchers and is trusted by 64 researchers here, as inferred from the citation graph.

Subfields

Whom Sungwon Kim trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Aäron van den Oord
  4. Yoshua Bengio
  5. Alex Graves
  6. Alex Krizhevsky
  7. Kaiming He
  8. Karen Simonyan
  9. Yann LeCun
  10. Ilya Sutskever

Who trusts Sungwon Kim overall

  1. Wei Ping
  2. Xu Tan
  3. Conor Durkan
  4. Kainan Peng
  5. Takuma Okamoto
  6. Hyungjin Chung
  7. Yi Ren
  8. Jingyun Liang
  9. Heeseung Kim
  10. Sang-Hoon Lee

Papers from Sungwon Kim's perspective

Ordered by how strongly the researchers Sungwon Kim 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. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. GENERATIVE ADVERSARIAL NETS

Their papers