Takaaki Saeki

Artificial Intelligence · 2022

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

Subfields

Whom Takaaki Saeki trusts overall

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

  1. Leo Breiman
  2. Alexis Conneau
  3. Takuya Akiba
  4. Wei-Ning Hsu
  5. Alexei Baevski
  6. Diederik P. Kingma
  7. Sanyuan Chen
  8. Geoffrey E. Hinton
  9. Abdel-rahman Mohamed

Who trusts Takaaki Saeki overall

  1. Hubert Siuzdak
  2. Edresson Casanova
  3. Zeqian Ju

Papers from Takaaki Saeki's perspective

Ordered by how strongly the researchers Takaaki Saeki 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. ImageNet classification with deep convolutional neural networks
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers