Dongwei Jiang

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 4 papers; trusts 55 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 108 citations into it; #20,390 of 35,345 by trust here, #16,166 by citations
• Signal Processing — 65 citations into it; #4,201 of 7,572 by trust here, #3,099 by citations
• Speech & Audio — 59 citations into it; #735 of 1,076 by trust here, #769 by citations
• Natural Language Processing — 39 citations into it
• Representation & Self-Supervised Learning — 21 citations into it; #3,059 of 3,145 by trust here, #2,516 by citations
• Model Architectures — 19 citations into it
• Computer Vision and Pattern Recognition — 13 citations into it
• Optimization & Training — 8 citations into it

Whom Dongwei Jiang trusts overall

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

1. Diederik P. Kingma
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Alex Graves
5. Jimmy Ba
6. J. Urgen Schmidhuber
7. Alex Krizhevsky
8. Ilya Sutskever
9. Yann LeCun
10. Kaiming He

Who trusts Dongwei Jiang overall

1. Andy T. Liu
2. Hung-yi Lee
3. Shang-Wen Li
4. Abdel-rahman Mohamed
5. Alexei Baevski
6. Demetres Kostas
7. Yung-Sung Chuang
8. Lasse Borgholt
9. Liping Chen
10. Zhiyun Fan

Papers from Dongwei Jiang's perspective

Ordered by how strongly the researchers Dongwei Jiang 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

• A Further Study of Unsupervised Pretraining for Transformer Based Speech Recognition (2020) — 32 citations
• Improving Transformer-based Speech Recognition Using Unsupervised Pre-training (2019) — 106 citations
• Didispeech: A Large Scale Mandarin Speech Corpus (2020) — 63 citations
• Comparable Study Of Modeling Units For End-To-End Mandarin Speech Recognition (2018) — 35 citations