Xu Yang

Computer Vision and Pattern Recognition · with Deng · 2019–2022

A researcher in the Science corpus: 6 papers; trusts 731 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 152 citations into it; #10,793 of 21,575 by trust here, #10,677 by citations
• Artificial Intelligence — 113 citations into it; #23,582 of 35,345 by trust here, #21,316 by citations
• Representation & Self-Supervised Learning — 62 citations into it
• Meta & Continual Learning — 20 citations into it
• Signal Processing — 17 citations into it
• Radiology, Nuclear Medicine and Imaging — 12 citations into it; #1,939 of 3,265 by trust here, #2,462 by citations
• Computational Mechanics — 9 citations into it
• Cognitive Neuroscience — 8 citations into it

Whom Xu Yang trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Yoshua Bengio
5. Yann LeCun
6. Diederik P. Kingma
7. Ilya Sutskever
8. Ross B. Girshick
9. Karen Simonyan
10. Andrew Zisserman

Who trusts Xu Yang overall

1. Cheng Deng
2. Yanan Gu
3. Fei Ye
4. Kun-Juan Wei
5. Lirong Wu
6. Adrian G. Bors
7. Liyuan Wang
8. Hongwei Yan
9. Yujie Wei
10. Zhangyang Gao

Papers from Xu Yang's perspective

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

Their papers

• Not Just Selection, but Exploration: Online Class-Incremental Continual Learning via Dual View Consistency (2022) — 106 citations
• Multi-Scale Fusion Subspace Clustering Using Similarity Constraint (2020) — 41 citations
• Heterogeneous Graph Attention Network for Unsupervised Multiple-Target Domain Adaptation (2020) — 153 citations
• Lifelong Zero-Shot Learning (2020) — 74 citations
• Saliency Detection via a Multiple Self-Weighted Graph-Based Manifold Ranking (2020) — 54 citations
• Deep Spectral Clustering Using Dual Autoencoder Network (2019) — 288 citations