Yoshiyasu Takefuji

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 32 researchers and is trusted by 19 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it; #7,856 of 35,345 by trust here, #11,490 by citations
• Natural Language Processing — 39 citations into it; #1,677 of 5,688 by trust here, #2,473 by citations
• Representation & Self-Supervised Learning — 20 citations into it; #2,108 of 3,145 by trust here, #2,691 by citations
• Information Systems — 8 citations into it
• Information Extraction — 7 citations into it
• Information Retrieval & Search — 5 citations into it

Whom Yoshiyasu Takefuji trusts overall

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

1. Andrew Chisholm
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Tomas Mikolov
5. Richard Socher
6. Felix Hill
7. David N. Milne
8. Kyunghyun Cho
9. Ilya Sutskever
10. Edgar Meij

Who trusts Yoshiyasu Takefuji overall

1. Phong Le
2. Samuel Broscheit
3. Ikuya Yamada
4. Jonathan Raiman
5. Ivan Titov
6. Nicola De Cao
7. Pedro Henrique Martins
8. Octavian-Eugen Ganea
9. Yasumasa Onoe

Papers from Yoshiyasu Takefuji's perspective

Ordered by how strongly the researchers Yoshiyasu Takefuji trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Long Short-Term Memory
4. ImageNet classification with deep convolutional neural networks
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
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. ImageNet: A large-scale hierarchical image database
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation (2016) — 337 citations
• Learning Distributed Representations of Texts and Entities from Knowledge Base (2017) — 103 citations