Junshan Wang

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 38 citations into it
• Graph Learning — 18 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Statistical and Nonlinear Physics — 17 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Molecular Biology — 7 citations into it

Whom Junshan Wang trusts overall

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

1. Santo Fortunato
2. Jeffrey Scott Vitter
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Rahaf Aljundi
6. David Lopez-Paz
7. Alex Krizhevsky
8. Bryan Perozzi
9. Diederik P. Kingma
10. William L. Hamilton

Papers from Junshan Wang's perspective

Ordered by how strongly the researchers Junshan 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Streaming Graph Neural Networks via Continual Learning (2020) — 148 citations
• Dynamic Network Embedding : An Extended Approach for Skip-gram based Network Embedding (2018) — 231 citations