Jun Wang

Artificial Intelligence · with Liu · 2019

A researcher in the Science corpus: 1 paper; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 10 citations into it
• Model Architectures — 7 citations into it
• Computer Vision and Pattern Recognition — 5 citations into it

Whom Jun Wang trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Kaiming He
4. Hirotugu Akaike
5. Helmut Ltkepohl
6. Ilya Sutskever
7. Vinod Nair

Papers from Jun Wang's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Long Short-Term Memory
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. Rectified Linear Units Improve Restricted Boltzmann Machines
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Multivariate Temporal Convolutional Network: A Deep Neural Networks Approach for Multivariate Time Series Forecasting (2019) — 347 citations