Yaguo Lei

Control and Systems Engineering · 2008–2020

A researcher in the Science corpus: 20 papers; trusts 50 researchers and is trusted by 47 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 193 citations into it; #355 of 8,257 by trust here, #72 by citations
• Mechanical Engineering — 113 citations into it; #804 of 8,300 by trust here, #1,488 by citations
• Artificial Intelligence — 93 citations into it
• Safety, Risk, Reliability and Quality — 60 citations into it; #965 of 1,220 by trust here, #141 by citations
• Statistics and Probability — 52 citations into it
• Mechanics of Materials — 49 citations into it; #697 of 6,291 by trust here, #266 by citations
• Computer Vision and Pattern Recognition — 43 citations into it
• Representation & Self-Supervised Learning — 28 citations into it

Whom Yaguo Lei trusts overall

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

1. Geoffrey E. Hinton
2. Naipeng Li
3. Vladimir Naumovich Vapnik
4. Yoshua Bengio
5. Kamal Medjaher
6. Richard Baraniuk
7. Yann LeCun
8. Alex Krizhevsky
9. Noureddine Zerhouni
10. Liang Guo

Who trusts Yaguo Lei overall

1. Haidong Shao
2. Shen Zhang
3. Long Wen
4. Xiang Li
5. Ruonan Liu
6. Jinyang Jiao
7. Te Han
8. Hongkai Jiang
9. Boyuan Yang
10. Ya-dong Xue

Papers from Yaguo Lei's perspective

Ordered by how strongly the researchers Yaguo Lei trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data (2016) — 1,047 citations
• Applications of machine learning to machine fault diagnosis: A review and roadmap (2020) — 2,573 citations
• A Hybrid Prognostics Approach for Estimating Remaining Useful Life of Rolling Element Bearings (2020) — 1,563 citations
• Deep separable convolutional network for remaining useful life prediction of machinery (2019) — 343 citations
• An intelligent fault diagnosis approach based on transfer learning from laboratory bearings to locomotive bearings (2019) — 758 citations
• Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data (2019) — 1,048 citations
• A probability distribution model of tooth pits for evaluating time-varying mesh stiffness of pitting gears (2018) — 112 citations
• A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines (2018) — 491 citations
• Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods (2018) — 609 citations
• Machinery health prognostics: A systematic review from data acquisition to RUL prediction (2018) — 2,251 citations
• Deep normalized convolutional neural network for imbalanced fault classification of machinery and its understanding via visualization (2018) — 547 citations
• A recurrent neural network based health indicator for remaining useful life prediction of bearings (2017) — 1,105 citations
• An underdamped stochastic resonance method with stable-state matching for incipient fault diagnosis of rolling element bearings (2017) — 141 citations
• Deep neural networks: A promising tool for fault characteristic mining and intelligent diagnosis of rotating machinery with massive data (2016) — 1,612 citations
• A Model-Based Method for Remaining Useful Life Prediction of Machinery (2016) — 526 citations
• An Improved Exponential Model for Predicting Remaining Useful Life of Rolling Element Bearings (2015) — 594 citations
• EEMD method and WNN for fault diagnosis of locomotive roller bearings (2011) — 305 citations
• Adaptive multiwavelets via two-scale similarity transforms for rotating machinery fault diagnosis (2009) — 50 citations
• Gear crack level identification based on weighted K nearest neighbor classification algorithm (2009) — 279 citations
• A new approach to intelligent fault diagnosis of rotating machinery (2008) — 402 citations