Pan Zhang

Artificial Intelligence · with Wang · 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 Pan Zhang 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

Papers from Pan Zhang's perspective

Ordered by how strongly the researchers Pan Zhang 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. GENERATIVE ADVERSARIAL NETS
3. ImageNet classification with deep convolutional neural networks
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Deep Learning
9. Learning Multiple Layers of Features from Tiny Images
10. AUTO-ENCODING VARIATIONAL BAYES

Their papers

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