Jun Wang

Artificial Intelligence · with Fan · 2017

A researcher in the Science corpus: 1 paper; trusts 11 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 14 citations into it
• Atomic and Molecular Physics, and Optics — 13 citations into it
• Probabilistic & Bayesian Methods — 13 citations into it
• Computer Vision and Pattern Recognition — 7 citations into it
• Condensed Matter Physics — 6 citations into it
• Statistical and Nonlinear Physics — 5 citations into it

Whom Jun Wang trusts overall

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

1. Geoffrey E. Hinton
2. Yann LeCun
3. Diederik P. Kingma
4. Aapo Hyvärinen
5. Paul Smolensky
6. John J. Hopfield
7. Ulrich Schollwoeck
8. Roman Orus
9. Yoshua Bengio
10. Ruslan Salakhutdinov

Who trusts Jun Wang overall

1. Marcello Benedetti

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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. ImageNet classification with deep convolutional neural networks
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
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

• Unsupervised Generative Modeling Using Matrix Product States (2017) — 313 citations