Ping Yu
Computer Vision and Pattern Recognition · with Chen · 2020
A researcher in the Science corpus: 2 papers; trusts 108 researchers and is trusted by 2 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 53 citations into it
- Artificial Intelligence — 46 citations into it
- Generative Models — 35 citations into it; #1,717 of 1,956 by trust here, #1,796 by citations
- Probabilistic & Bayesian Methods — 16 citations into it
- Optimization & Training — 12 citations into it
- Representation & Self-Supervised Learning — 6 citations into it
- Statistics and Probability — 5 citations into it
Whom Ping Yu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Max Welling
- Kaiming He
- Yann LeCun
- Ilya Sutskever
- J. Urgen Schmidhuber
- Karen Simonyan
Who trusts Ping Yu overall
Papers from Ping Yu's perspective
Ordered by how strongly the researchers Ping Yu 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)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Learning Multiple Layers of Features from Tiny Images
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Feature Quantization Improves GAN Training (2020) — 50 citations
- Bayesian Meta Sampling for Fast Uncertainty Adaptation (2020) — 13 citations