Dichao Hu

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 155 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it; #14,109 of 35,345 by trust here, #25,809 by citations
• Natural Language Processing — 21 citations into it; #2,626 of 5,688 by trust here, #4,682 by citations
• Model Architectures — 11 citations into it; #1,031 of 2,278 by trust here, #1,976 by citations
• Computer Vision and Pattern Recognition — 8 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Dichao Hu trusts overall

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

1. Alex Graves
2. Yoshua Bengio
3. Tomas Mikolov
4. Ilya Sutskever
5. Geoffrey E. Hinton
6. Kyunghyun Cho
7. Nal Kalchbrenner
8. Diederik P. Kingma
9. Kaiming He
10. Alex Krizhevsky

Who trusts Dichao Hu overall

1. S. M. Mousavi
2. William Ellsworth
3. Alana de Santana Correia
4. Gianni Brauwers
5. Federico A. Galatolo
6. Weiqiang Zhu
7. Tianlin Zhang
8. Salman Hameed Khan
9. Yanjun Huang
10. Wei Tao

Papers from Dichao Hu's perspective

Ordered by how strongly the researchers Dichao Hu 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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• An Introductory Survey on Attention Mechanisms in NLP Problems (2018) — 276 citations