Shiyu Zhou

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 5 papers; trusts 124 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 105 citations into it; #14,101 of 35,345 by trust here, #13,962 by citations
• Signal Processing — 47 citations into it; #4,362 of 7,572 by trust here, #2,743 by citations
• Computer Vision and Pattern Recognition — 45 citations into it
• Natural Language Processing — 43 citations into it; #4,964 of 5,688 by trust here, #4,183 by citations
• Speech & Audio — 31 citations into it; #677 of 1,076 by trust here, #731 by citations
• Model Architectures — 25 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Large Language Models — 9 citations into it

Whom Shiyu Zhou trusts overall

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

1. Diederik P. Kingma
2. Alex Graves
3. Geoffrey E. Hinton
4. Jimmy Ba
5. Yoshua Bengio
6. Christian Szegedy
7. Yann LeCun
8. Alex Krizhevsky
9. Ilya Sutskever
10. Ashish Vaswani

Who trusts Shiyu Zhou overall

1. Linhao Dong
2. Davis Liang
3. Ahmed M. Ali
4. Biao Zhang
5. Naihan Li
6. Zhiheng Huang
7. Shigeki Karita
8. Kyu J. Han
9. Ye Bai
10. Xu Tan

Papers from Shiyu Zhou's perspective

Ordered by how strongly the researchers Shiyu Zhou 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Syllable-Based Sequence-to-Sequence Speech Recognition with the Transformer in Mandarin Chinese (2018) — 130 citations
• OPT: Omni-Perception Pre-Trainer for Cross-Modal Understanding and Generation (2021) — 41 citations
• Exploring wav2vec 2.0 on speaker verification and language identification (2020) — 244 citations
• A Comparison of Modeling Units in Sequence-to-Sequence Speech Recognition with the Transformer on Mandarin Chinese (2018) — 69 citations
• Extending Recurrent Neural Aligner for Streaming End-to-End Speech Recognition in Mandarin (2018) — 23 citations