Shuoyang Ding

Artificial Intelligence · 2016–2019

A researcher in the Science corpus: 5 papers; trusts 161 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 90 citations into it; #10,295 of 35,345 by trust here, #15,866 by citations
• Natural Language Processing — 79 citations into it; #2,809 of 5,688 by trust here, #4,449 by citations
• Computer Vision and Pattern Recognition — 31 citations into it; #13,626 of 21,575 by trust here, #19,310 by citations
• Signal Processing — 22 citations into it
• Speech & Audio — 21 citations into it; #783 of 1,076 by trust here, #869 by citations
• Model Architectures — 15 citations into it
• Safety, Robustness & Interpretability — 6 citations into it

Whom Shuoyang Ding trusts overall

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

1. Yoshua Bengio
2. Dzmitry Bahdanau
3. Philipp Koehn
4. Geoffrey E. Hinton
5. Franz Joseph Och
6. Rico Sennrich
7. Kyunghyun Cho
8. Ilya Sutskever
9. Diederik P. Kingma
10. Alex Graves

Who trusts Shuoyang Ding overall

1. Philipp Koehn
2. Danielle Saunders
3. Huda Khayrallah
4. Masoud Jalili Sabet
5. Sarah Wiegreffe
6. Pooya Moradi
7. Stéphane Clinchant
8. Sachin Kumar
9. Jinyu Li
10. Shinji Watanabe

Papers from Shuoyang Ding's perspective

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

Their papers

• Multi-Modal Data Augmentation for End-to-end ASR (2018) — 40 citations
• Saliency-driven Word Alignment Interpretation for Neural Machine Translation (2019) — 63 citations
• The JHU Machine Translation Systems for WMT 2016 (2016) — 20 citations
• A Call for Prudent Choice of Subword Merge Operations in Neural Machine Translation (2019) — 73 citations
• Low Resource Multi-modal Data Augmentation for End-to-end ASR (2018) — 29 citations