Takao Murakami

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Takao Murakami trusts overall

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

  1. Peter Kairouz
  2. Jianhua Lin
  3. Dakshi Agrawal
  4. Trevor J. Hastie
  5. Weiran Wang
  6. Yong Bao
  7. John C. Duchi
  8. Cynthia Dwork
  9. Ú. Erlingsson
  10. Andrew Gelman

Who trusts Takao Murakami overall

  1. Maria Rigaki

Papers from Takao Murakami's perspective

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

Their papers