Takeshi Sakaki

Statistical and Nonlinear Physics · 2010–2013

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 35 researchers here, as inferred from the citation graph.

Subfields

Whom Takeshi Sakaki trusts overall

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

  1. Thorsten Joachims
  2. Jure Leskovec
  3. Pavel Serdyukov
  4. Dieter Fox
  5. Jeffrey Hightower
  6. Bernardo A. Huberman
  7. Lada A. Adamic
  8. M. Sanjeev Arulampalam
  9. Vanessa Murdock
  10. Qiaozhu Mei

Who trusts Takeshi Sakaki overall

  1. Hila Becker
  2. Mor Naaman
  3. Carlos Castillo
  4. Aditi Gupta
  5. Andrew T. Crooks
  6. Manish Gupta
  7. Linna Li
  8. Yoav Artzi
  9. Paul Earle
  10. Haji Mohammad Saleem

Papers from Takeshi Sakaki's perspective

Ordered by how strongly the researchers Takeshi Sakaki 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. Attention is All you Need (Neural Information Processing Systems)
  4. Long Short-Term Memory
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  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