Binxuan Huang

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 87 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 36 citations into it; #33,162 of 35,345 by trust here, #23,077 by citations
• Natural Language Processing — 21 citations into it
• Model Architectures — 8 citations into it
• Optimization & Training — 5 citations into it

Whom Binxuan Huang trusts overall

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

1. Diederik P. Kingma
2. Duyu Tang
3. Geoffrey E. Hinton
4. Christopher D. Manning
5. Richard Socher
6. Yoshua Bengio
7. Jeffrey Pennington
8. Jimmy Ba
9. Ilya Sutskever
10. Alex Krizhevsky

Who trusts Binxuan Huang overall

1. Ruifan Li
2. Hao Tang
3. Zhengjie Gao
4. Qingshan Jiang
5. Kathleen M. Carley
6. Hao Chen
7. Donghong Ji
8. Ao Feng
9. Lei-tai Chen
10. Fangxiang Feng

Papers from Binxuan Huang's perspective

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

Their papers

• Syntax-Aware Aspect Level Sentiment Classification with Graph Attention Networks (2019) — 300 citations
• Aspect Level Sentiment Classification with Attention-over-Attention Neural Networks (2018) — 359 citations