Seunghwa Beack

Computer Vision and Pattern Recognition · 2018

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Seunghwa Beack trusts overall

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

  1. Diederik P. Kingma
  2. Johannes Ballé
  3. Aäron van den Oord
  4. Jimmy Ba
  5. Geoffrey E. Hinton
  6. Nick Johnston

Who trusts Seunghwa Beack overall

  1. Chris J. Maddison
  2. Benjamin Bloem-Reddy
  3. Yann Dubois

Papers from Seunghwa Beack's perspective

Ordered by how strongly the researchers Seunghwa Beack trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. GENERATIVE ADVERSARIAL NETS
  4. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
  5. ImageNet classification with deep convolutional neural networks
  6. Gradient-based learning applied to document recognition
  7. Long Short-Term Memory
  8. ImageNet: A large-scale hierarchical image database
  9. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
  10. Attention is All you Need (Neural Information Processing Systems)

Their papers