Xinmin Wang

Artificial Intelligence · 2019

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

Subfields

• Artificial Intelligence — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Xinmin Wang trusts overall

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

1. Yoshua Bengio
2. L. Eon Bottou
3. Geoffrey E. Hinton
4. Sergey Ioffe
5. Kaiming He
6. Xavier Glorot
7. Vinod Nair
8. Christian Szegedy
9. Arnaud Delorme
10. Fabien Lotte

Papers from Xinmin Wang's perspective

Ordered by how strongly the researchers Xinmin 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Rectified Linear Units Improve Restricted Boltzmann Machines

Their papers

• EEG-Based Spatio–Temporal Convolutional Neural Network for Driver Fatigue Evaluation (2019) — 412 citations