Haopeng Zhang

Artificial Intelligence · with Zhang · 2020

A researcher in the Science corpus: 2 papers; trusts 101 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 41 citations into it; #26,904 of 35,345 by trust here, #24,417 by citations
• Graph Learning — 17 citations into it
• Natural Language Processing — 16 citations into it
• Model Architectures — 12 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it; #16,488 of 21,575 by trust here, #17,258 by citations
• Molecular Biology — 8 citations into it

Whom Haopeng Zhang trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Yann LeCun
5. Yoon Kim
6. Richard Socher
7. Jimmy Ba
8. Alex Krizhevsky
9. Ilya Sutskever
10. Jacob Devlin

Who trusts Haopeng Zhang overall

1. Yuxiao Lin
2. Chengxuan Ying
3. Vijay Prakash Dwivedi
4. Dexiong Chen
5. Yuxian Meng

Papers from Haopeng Zhang's perspective

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

Their papers

• Text Graph Transformer for Document Classification (2020) — 75 citations
• Graph-Bert: Only Attention is Needed for Learning Graph Representations (2020) — 391 citations