Tao Yan
Control and Systems Engineering · with Li · 2018–2019
A researcher in the Science corpus: 3 papers; trusts 9 researchers and is trusted by 4 researchers here, as inferred from the citation graph.
Subfields
- Control and Systems Engineering — 60 citations into it; #5,276 of 8,257 by trust here, #1,670 by citations
- Mechanical Engineering — 30 citations into it
- Artificial Intelligence — 24 citations into it
- Mechanics of Materials — 23 citations into it
- Representation & Self-Supervised Learning — 8 citations into it
Whom Tao Yan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Tao Yan overall
Papers from Tao Yan's perspective
Ordered by how strongly the researchers Tao Yan trusts endorse each paper. Same corpus, a different order for every researcher.
- A Survey on Transfer Learning
- ImageNet classification with deep convolutional neural networks
- Domain-Adversarial Training of Neural Networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Deep Domain Confusion: Maximizing for Domain Invariance
- Gradient-based learning applied to document recognition
- Residual life predictions from vibration-based degradation signals: a neural network approach (IEEE transactions on industrial electronics (1982. Print))
- Domain Adaptation via Transfer Component Analysis
- A theory of learning from different domains
- Long Short-Term Memory
Their papers
- Deep separable convolutional network for remaining useful life prediction of machinery (2019) — 343 citations
- Deep Convolutional Transfer Learning Network: A New Method for Intelligent Fault Diagnosis of Machines With Unlabeled Data (2019) — 1,048 citations
- Machinery health prognostics: A systematic review from data acquisition to RUL prediction (2018) — 2,251 citations