Makoto Miwa

Artificial Intelligence · 2014–2017

A researcher in the Science corpus: 4 papers; trusts 81 researchers and is trusted by 125 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it; #2,035 of 35,345 by trust here, #8,706 by citations
• Natural Language Processing — 20 citations into it; #698 of 5,688 by trust here, #2,364 by citations
• Optimization & Training — 9 citations into it
• Model Architectures — 8 citations into it
• Information Extraction — 7 citations into it
• Management Science and Operations Research — 6 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Makoto Miwa trusts overall

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

1. Michael Collins
2. Alex Graves
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Dan Roth
7. Lev-Arie Ratinov
8. Ilya Sutskever
9. Alex Krizhevsky
10. Jimmy Ba

Who trusts Makoto Miwa overall

1. Arzoo Katiyar
2. Tsu-Jui Fu
3. Yi Luan
4. Ben Goodrich
5. Giannis Bekoulis
6. Lu Xu
7. Zexuan Zhong
8. Luheng He
9. Zhepei Wei
10. Suncong Zheng

Papers from Makoto Miwa's perspective

Ordered by how strongly the researchers Makoto Miwa 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. Attention is All you Need (Neural Information Processing Systems)
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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures (2016) — 1,268 citations
• Modeling Joint Entity and Relation Extraction with Table Representation (2014) — 338 citations
• Extracting Drug-Drug Interactions with Attention CNNs (2017) — 45 citations
• Using text mining for study identification in systematic reviews: a systematic review of current approaches (2015) — 672 citations