Min Xia

Control and Systems Engineering · IEEE Transactions on Industrial Informatics · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Min Xia trusts overall

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

  1. A. Głowacz
  2. Andrew L. Maas
  3. Chuang Sun
  4. Weicong Kong
  5. Cyril Voyant
  6. Haidong Shao
  7. Matthew D. Zeiler
  8. Ruqiang Yan
  9. Stephen Marcus McAleer
  10. Zhao Yang Dong

Papers from Min Xia's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Long Short-Term Memory
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. Rectifier Nonlinearities Improve Neural Network Acoustic Models
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  10. Highly Accurate Machine Fault Diagnosis Using Deep Transfer Learning (IEEE Transactions on Industrial Informatics)

Their papers