Naoya Takahashi

Signal Processing · 2017–2020

A researcher in the Science corpus: 6 papers; trusts 122 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

Whom Naoya Takahashi trusts overall

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

  1. Alex Krizhevsky
  2. Emmanuel Vincent
  3. Stefan Uhlich
  4. Christian Szegedy
  5. Geoffrey E. Hinton
  6. Sergey Ioffe
  7. Yuki Mitsufuji
  8. Kaiming He
  9. Yoshua Bengio
  10. Aditya Arie Nugraha

Who trusts Naoya Takahashi overall

  1. Alexandre D'efossez
  2. Hyeong-Seok Choi
  3. Jen-Yu Liu
  4. Yuki Mitsufuji
  5. Shota Horiguchi
  6. Nicolas Usunier
  7. Yi-Hsuan Yang
  8. Laure Prétet
  9. David Samuel
  10. Simon Rouard

Papers from Naoya Takahashi's perspective

Ordered by how strongly the researchers Naoya Takahashi 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. Long Short-Term Memory
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Going deeper with convolutions
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers