Junwen Duan

Artificial Intelligence · 2014–2016

A researcher in the Science corpus: 3 papers; trusts 46 researchers and is trusted by 40 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 32 citations into it
• Management Science and Operations Research — 21 citations into it; #2,275 of 11,946 by trust here, #4,921 by citations
• Natural Language Processing — 19 citations into it
• Finance — 16 citations into it
• Graph Learning — 11 citations into it
• Representation & Self-Supervised Learning — 10 citations into it
• Time-Series & Forecasting — 10 citations into it; #36 of 381 by trust here, #34 by citations
• Economics and Econometrics — 8 citations into it; #5,265 of 23,481 by trust here, #12,444 by citations

Whom Junwen Duan trusts overall

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

1. Yoshua Bengio
2. Antoine Bordes
3. Yue Zhang
4. Tomas Mikolov
5. Xiao Ding
6. Geoffrey E. Hinton
7. Jason Aaron Edward Weston
8. Ronny Luss
9. Richard Socher
10. Ilya Sutskever

Who trusts Junwen Duan overall

1. Weiwei Jiang
2. Xiao Ding
3. Leonardo dos Santos Pinheiro
4. Yumo Xu
5. Omer Berat Sezer
6. Xi Zhang
7. Ting-Wei Liu
8. Ryo Akita
9. Takashi Matsubara
10. Ishan Verma

Papers from Junwen Duan's perspective

Ordered by how strongly the researchers Junwen Duan 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. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Using Structured Events to Predict Stock Price Movement: An Empirical Investigation (2014) — 256 citations
• Knowledge-Driven Event Embedding for Stock Prediction (2016) — 126 citations
• Deep Learning for Event-Driven Stock Prediction (2015) — 832 citations