Liang Guo

Control and Systems Engineering · Neurocomputing · 2017–2019

A researcher in the Science corpus: 4 papers; trusts 9 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Control and Systems Engineering — 61 citations into it; #3,723 of 8,257 by trust here, #566 by citations
• Mechanical Engineering — 25 citations into it; #3,409 of 8,300 by trust here, #2,836 by citations
• Artificial Intelligence — 24 citations into it
• Mechanics of Materials — 23 citations into it; #2,903 of 6,291 by trust here, #886 by citations
• Representation & Self-Supervised Learning — 9 citations into it

Whom Liang Guo trusts overall

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

1. Sinno Jialin Pan
2. Yaguo Lei
3. Hai Qiu
4. Naipeng Li
5. Eric Tzeng
6. Vladimir Naumovich Vapnik
7. Weining Lu
8. Yaroslav Ganin
9. Feng Jia
10. Tarak Benkedjouh

Who trusts Liang Guo overall

1. Shen Zhang
2. Yaguo Lei
3. Dhiraj Neupane
4. Shibo Zhang
5. Biao Wang
6. Jun Zhu
7. Jinyang Jiao
8. Bingnan Wang
9. Rui Yang
10. Naipeng Li

Papers from Liang Guo's perspective

Ordered by how strongly the researchers Liang Guo 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data (2019) — 1,048 citations
• A neural network constructed by deep learning technique and its application to intelligent fault diagnosis of machines (2018) — 491 citations
• Machinery health prognostics: A systematic review from data acquisition to RUL prediction (2018) — 2,251 citations
• A recurrent neural network based health indicator for remaining useful life prediction of bearings (2017) — 1,105 citations