Takehisa Yairi

Artificial Intelligence · 2006–2018

A researcher in the Science corpus: 5 papers; trusts 53 researchers and is trusted by 80 researchers here, as inferred from the citation graph.

Subfields

Whom Takehisa Yairi trusts overall

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

  1. Chih-Jen Lin
  2. Steven L. Brunton
  3. J. Nathan Kutz
  4. Mark A. Kramer
  5. Heiko Hoffmann
  6. Clarence W. Rowley
  7. Malte Kuss
  8. Diederik P. Kingma
  9. Geoffrey E. Hinton
  10. Igor Mezi'c

Who trusts Takehisa Yairi overall

  1. Renwei Dian
  2. Shen Zhang
  3. Shutao Li
  4. Liron Bergman
  5. Pramuditha Perera
  6. Kilian Batzner
  7. Sebastian Schmidl
  8. Jonathan Ko
  9. Andrew Cook
  10. Jacopo Castellini

Papers from Takehisa Yairi's perspective

Ordered by how strongly the researchers Takehisa Yairi 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  6. Long Short-Term Memory
  7. Attention is All you Need (Neural Information Processing Systems)
  8. ImageNet: A large-scale hierarchical image database
  9. Learning Multiple Layers of Features from Tiny Images
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers