Jun-Kun Wang

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jun-Kun Wang trusts overall

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

  1. Elad Hazan
  2. Simon Lacoste-Julien
  3. Guanghui Lan
  4. Martin Jaggi
  5. Dan Garber
  6. Seyoung Kim
  7. Yurii E. Nesterov
  8. F. Maxwell Harper
  9. B. Recht
  10. Vasileios Belagiannis

Papers from Jun-Kun Wang's perspective

Ordered by how strongly the researchers Jun-Kun Wang trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet: A large-scale hierarchical image database
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Long Short-Term Memory
  8. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers