Yaoqing Yang
Computer Vision and Pattern Recognition · 2017–2021
A researcher in the Science corpus: 7 papers; trusts 308 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 111 citations into it
- Computational Mechanics — 84 citations into it; #1,871 of 10,001 by trust here, #792 by citations
- Artificial Intelligence — 83 citations into it
- Graph Learning — 52 citations into it
- Aerospace Engineering — 32 citations into it
- Geology — 31 citations into it; #132 of 687 by trust here, #86 by citations
- Statistical and Nonlinear Physics — 25 citations into it
- 3D Vision & Pose — 24 citations into it
Whom Yaoqing Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Charles Ruizhongtai Qi
- Yann LeCun
- Alex Krizhevsky
- Yoshua Bengio
- Kaiming He
- Diederik P. Kingma
- L. V. D. van der Maaten
- Hao Su
- Ilya Sutskever
Who trusts Yaoqing Yang overall
- Zhiqin Chen
- Haowen Deng
- Yongming Rao
- Zhiyuan Zhang
- Jonathan Sauder
- Zhizhong Han
- Yan Zhang
- Yifan Wang
- Saining Xie
- Minghua Liu
Papers from Yaoqing Yang's perspective
Ordered by how strongly the researchers Yaoqing Yang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks (2021) — 309 citations
- Cross-Iteration Coded Computing (2018) — 15 citations
- FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation (2017) — 1,401 citations
- Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling (2017) — 532 citations
- Neighbors Do Help: Deeply Exploiting Local Structures of Point Clouds (2017) — 33 citations
- Coded Distributed Computing for Inverse Problems (2017) — 68 citations
- FoldingNet: Interpretable Unsupervised Learning on 3D Point Clouds (2017) — 84 citations