Xiao Ding

Artificial Intelligence · with Liu · 2014–2020

A researcher in the Science corpus: 8 papers; trusts 194 researchers and is trusted by 44 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 104 citations into it; #27,159 of 35,345 by trust here, #22,463 by citations
• Natural Language Processing — 88 citations into it; #4,003 of 5,688 by trust here, #3,977 by citations
• Computer Vision and Pattern Recognition — 31 citations into it
• Molecular Biology — 25 citations into it; #14,266 of 17,773 by trust here, #17,476 by citations
• Management Science and Operations Research — 22 citations into it; #2,274 of 11,946 by trust here, #4,921 by citations
• Representation & Self-Supervised Learning — 22 citations into it
• Graph Learning — 18 citations into it
• Finance — 16 citations into it

Whom Xiao Ding trusts overall

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

1. Yoshua Bengio
2. Tomas Mikolov
3. Ilya Sutskever
4. Geoffrey E. Hinton
5. Antoine Bordes
6. Yue Zhang
7. Diederik P. Kingma
8. Alex Krizhevsky
9. Jason Aaron Edward Weston
10. Richard Socher

Who trusts Xiao Ding overall

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

Papers from Xiao Ding's perspective

Ordered by how strongly the researchers Xiao Ding 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

• Constructing Narrative Event Evolutionary Graph for Script Event Prediction (2018) — 218 citations
• DectICO: an alignment-free supervised metagenomic classification method based on feature extraction and dynamic selection (2015) — 11 citations
• Using Structured Events to Predict Stock Price Movement: An Empirical Investigation (2014) — 256 citations
• Guided Generation of Cause and Effect (2020) — 89 citations
• Story Ending Prediction by Transferable BERT (2019) — 54 citations
• Generating Reasonable and Diversified Story Ending Using Sequence to Sequence Model with Adversarial Training (2018) — 42 citations
• Knowledge-Driven Event Embedding for Stock Prediction (2016) — 126 citations
• Deep Learning for Event-Driven Stock Prediction (2015) — 832 citations