Kazuki Yoshiyama

Computer Vision and Pattern Recognition · 2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kazuki Yoshiyama trusts overall

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

  1. Alex Krizhevsky
  2. Radford M. Neal

Papers from Kazuki Yoshiyama's perspective

Ordered by how strongly the researchers Kazuki Yoshiyama 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. Learning Multiple Layers of Features from Tiny Images
  3. ImageNet: A large-scale hierarchical image database
  4. ImageNet classification with deep convolutional neural networks
  5. Gradient-based learning applied to document recognition
  6. Categorical Reparameterization with Gumbel-Softmax
  7. Pattern Recognition and Machine Learning
  8. The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
  9. Estimating or Propagating Gradients Through Stochastic Neurons for Conditional Computation
  10. Long Short-Term Memory

Their papers