Chuang Sun

Artificial Intelligence · 2017–2020

A researcher in the Science corpus: 5 papers; trusts 103 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 67 citations into it
• Control and Systems Engineering — 49 citations into it
• Computer Vision and Pattern Recognition — 45 citations into it
• Mechanical Engineering — 30 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Model Architectures — 15 citations into it
• Mechanics of Materials — 12 citations into it
• Optimization & Training — 9 citations into it

Whom Chuang Sun trusts overall

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

1. Yann LeCun
2. Geoffrey E. Hinton
3. Alex Krizhevsky
4. Yoshua Bengio
5. Kaiming He
6. Ilya Sutskever
7. J. Urgen Schmidhuber
8. Diederik P. Kingma
9. Karen Simonyan
10. L. Eon Bottou

Who trusts Chuang Sun overall

1. Min Xia
2. Yuchen Jiang
3. Haidong Shao
4. Shen Zhang

Papers from Chuang Sun's perspective

Ordered by how strongly the researchers Chuang Sun 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
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 Learning Algorithms for Rotating Machinery Intelligent Diagnosis: An Open Source Benchmark Study (2020) — 588 citations
• Deep Transfer Learning Based on Sparse Autoencoder for Remaining Useful Life Prediction of Tool in Manufacturing (2019) — 434 citations
• Applications of Unsupervised Deep Transfer Learning to Intelligent Fault Diagnosis: A Survey and Comparative Study (2019) — 505 citations
• WaveletKernelNet: An Interpretable Deep Neural Network for Industrial Intelligent Diagnosis (2019) — 515 citations
• Dislocated Time Series Convolutional Neural Architecture: An Intelligent Fault Diagnosis Approach for Electric Machine (2017) — 316 citations