Wenchao Yu

Artificial Intelligence · 2013–2020

A researcher in the Science corpus: 5 papers; trusts 56 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 105 citations into it
• Graph Learning — 53 citations into it
• Computer Vision and Pattern Recognition — 39 citations into it
• Statistical and Nonlinear Physics — 39 citations into it
• Representation & Self-Supervised Learning — 30 citations into it
• Molecular Biology — 12 citations into it
• Generative Models — 10 citations into it
• Computer Networks and Communications — 7 citations into it

Whom Wenchao Yu trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Yann LeCun
4. Tomas Mikolov
5. Diederik P. Kingma
6. Alex Krizhevsky
7. Ilya Sutskever
8. Ruslan Salakhutdinov
9. Ronald J. Williams
10. Sam T. Roweis

Who trusts Wenchao Yu overall

1. Yixin Liu
2. Tim Sainburg
3. Xiaoxiao Ma

Papers from Wenchao Yu's perspective

Ordered by how strongly the researchers Wenchao Yu 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Parameterized Explainer for Graph Neural Network (2020) — 824 citations
• Learning to Drop: Robust Graph Neural Network via Topological Denoising (2020) — 323 citations
• Robust Graph Representation Learning via Neural Sparsification (2020) — 338 citations
• NetWalk: A Flexible Deep Embedding Approach for Anomaly Detection in Dynamic Networks (2018) — 406 citations
• Embedding with Autoencoder Regularization (2013) — 48 citations