Xiao-Lei Zhang

Artificial Intelligence · 2013–2020

A researcher in the Science corpus: 4 papers; trusts 338 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 108 citations into it; #5,077 of 35,345 by trust here, #16,166 by citations
• Signal Processing — 94 citations into it; #1,821 of 7,572 by trust here, #3,566 by citations
• Speech & Audio — 33 citations into it
• Representation & Self-Supervised Learning — 31 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it; #5,237 of 21,575 by trust here, #17,258 by citations
• Computational Mechanics — 21 citations into it
• Evaluation & Benchmarks — 10 citations into it
• Model Architectures — 10 citations into it

Whom Xiao-Lei Zhang trusts overall

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

1. Yoshua Bengio
2. Geoffrey E. Hinton
3. Andrew Y. Ng
4. Michael I. Jordan
5. Ilya Sutskever
6. Alex Krizhevsky
7. Dong Yu
8. Francis R. Bach
9. Yann LeCun
10. Diederik P. Kingma

Who trusts Xiao-Lei Zhang overall

1. Xianchao Zhang
2. Xiaotong Zhang
3. Yu Zhang
4. 刘晗
5. Yi Luo
6. Anan Liu
7. Yuzhou Liu
8. Ido Ariav
9. Qiang Yang
10. Zheng-Hua Tan

Papers from Xiao-Lei Zhang's perspective

Ordered by how strongly the researchers Xiao-Lei Zhang 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deep Belief Networks Based Voice Activity Detection (2013) — 328 citations
• Speaker recognition based on deep learning: An overview (2020) — 406 citations
• A Deep Ensemble Learning Method for Monaural Speech Separation (2016) — 203 citations
• Convex Discriminative Multitask Clustering (2013) — 58 citations