Zhen Wang

Artificial Intelligence · with Chen · 2014–2020

A researcher in the Science corpus: 4 papers; trusts 39 researchers and is trusted by 61 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it; #3,758 of 35,345 by trust here, #4,393 by citations
• Natural Language Processing — 42 citations into it; #3,993 of 5,688 by trust here, #3,282 by citations
• Representation & Self-Supervised Learning — 21 citations into it
• Graph Learning — 13 citations into it; #116 of 693 by trust here, #134 by citations
• Molecular Biology — 8 citations into it
• Knowledge Graphs & Representation — 7 citations into it
• Information Retrieval & Search — 5 citations into it

Whom Zhen Wang trusts overall

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

1. Antoine Bordes
2. Jason Aaron Edward Weston
3. Richard Socher
4. Yoshua Bengio
5. Tomas Mikolov
6. Christopher D. Manning
7. Geoffrey E. Hinton
8. Ilya Sutskever
9. Sebastian Riedel
10. Mike D. Mintz

Who trusts Zhen Wang overall

1. Ruobing Xie
2. Hongwei Wang
3. Zhiyuan Liu
4. Liang Yao
5. Kristina Toutanova
6. Baoxu Shi
7. Quan Wang
8. Guoliang Ji
9. Yankai Lin
10. Zequn Sun

Papers from Zhen Wang's perspective

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

Their papers

• Knowledge Graph Embedding by Translating on Hyperplanes (2014) — 4,058 citations
• Knowledge Graph and Text Jointly Embedding (2014) — 401 citations
• AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search (2020) — 112 citations
• Aligning Knowledge and Text Embeddings by Entity Descriptions (2015) — 165 citations