Wei Wang

Artificial Intelligence · with Han · 2019

A researcher in the Science corpus: 1 paper; trusts 19 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it
• Computer Vision and Pattern Recognition — 23 citations into it
• Signal Processing — 19 citations into it
• Management Science and Operations Research — 16 citations into it
• Model Architectures — 15 citations into it
• Control and Systems Engineering — 8 citations into it
• Economics and Econometrics — 6 citations into it

Whom Wei Wang trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Yann LeCun
4. Alex Graves
5. Ilya Sutskever
6. J. Urgen Schmidhuber
7. Alex Krizhevsky
8. Diederik P. Kingma
9. Vladimir Naumovich Vapni
10. Sepp Hochreiter

Papers from Wei Wang's perspective

Ordered by how strongly the researchers Wei Wang 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. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Attention is All you Need (Neural Information Processing Systems)
7. GENERATIVE ADVERSARIAL NETS
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Review of Deep Learning Models for Time Series Prediction (2019) — 455 citations