Chongmin Wang

Mechanical Engineering · with Lim · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Mechanical Engineering — 53 citations into it
• Automotive Engineering — 38 citations into it

Whom Chongmin Wang trusts overall

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

1. J. Gardan
2. L. Thijs
3. Sasan Dadbakhsh
4. Yann LeCun
5. S. Tammas-Williams
6. Yoshua Bengio
7. Luke Scime
8. Geoffrey E. Hinton
9. X. Tan
10. Dimitris C. Lagoudas

Papers from Chongmin Wang's perspective

Ordered by how strongly the researchers Chongmin Wang 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. Going deeper with convolutions
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Machine learning in additive manufacturing: State-of-the-art and perspectives (2020) — 651 citations
• Additive manufacturing of NiTi shape memory alloys using pre-mixed powders (2019) — 194 citations