Carl Yang

Artificial Intelligence · 2017–2021

A researcher in the Science corpus: 4 papers; trusts 65 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 92 citations into it
• Graph Learning — 43 citations into it
• Computer Vision and Pattern Recognition — 34 citations into it
• Representation & Self-Supervised Learning — 31 citations into it
• Information Systems — 30 citations into it
• Generative Models — 19 citations into it
• Statistical and Nonlinear Physics — 19 citations into it
• Molecular Biology — 17 citations into it

Whom Carl Yang trusts overall

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

1. Geoffrey E. Hinton
2. Thomas Kipf
3. Yoshua Bengio
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Ilya Sutskever
7. Max Welling
8. Kaiming He
9. Tomas Mikolov
10. Yann LeCun

Who trusts Carl Yang overall

1. Ke Zhang
2. Shuai Zhang
3. Lichao Sun
4. Lina Yao

Papers from Carl Yang's perspective

Ordered by how strongly the researchers Carl Yang 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. ImageNet classification with deep convolutional neural networks
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Secure Deep Graph Generation with Link Differential Privacy (2020) — 52 citations
• Subgraph Federated Learning with Missing Neighbor Generation (2021) — 297 citations
• Conditional Structure Generation through Graph Variational Generative Adversarial Nets (2019) — 114 citations
• Bridging Collaborative Filtering and Semi-Supervised Learning: A Neural Approach for POI Recommendation (2017) — 316 citations