Daehan Won

2018

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Whom Daehan Won trusts overall

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

  1. Andrew L. Maas
  2. Cédric Villani

Who trusts Daehan Won overall

  1. Arvid Lundervold

Papers from Daehan Won's perspective

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

  1. Dropout: a simple way to prevent neural networks from overfitting
  2. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
  3. Best practices for convolutional neural networks applied to visual document analysis
  4. InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets
  5. Rectifier Nonlinearities Improve Neural Network Acoustic Models
  6. Wasserstein Generative Adversarial Networks
  7. Optimal Transport: Old and New
  8. BEGAN: Boundary Equilibrium Generative Adversarial Networks
  9. Current status and future potential of computer-aided diagnosis in medical imaging. (British Journal of Radiology)
  10. Medical Image Synthesis with Context-Aware Generative Adversarial Networks

Their papers