Chenglin Yang
Computer Vision and Pattern Recognition · 2018
A researcher in the Science corpus: 3 papers; trusts 519 researchers and is trusted by 6 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 113 citations into it; #12,282 of 21,575 by trust here, #12,172 by citations
- Artificial Intelligence — 91 citations into it; #19,608 of 35,345 by trust here, #18,186 by citations
- Model Architectures — 39 citations into it
- Optimization & Training — 33 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
- Evaluation & Benchmarks — 11 citations into it
- Efficiency & Compression — 9 citations into it; #1,088 of 1,264 by trust here, #1,081 by citations
- Media Technology — 6 citations into it
Whom Chenglin Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Kaiming He
- Ross B. Girshick
- Christian Szegedy
- Karen Simonyan
- Sergey Ioffe
- Jia Deng
- Ilya Sutskever
- Yoshua Bengio
Who trusts Chenglin Yang overall
- Jianping Gou
- Lin Wang
- Baosheng Yu
- Xu Tan
- Chenyu You
- Han-Jia Ye
- Siyuan Qiao
- S. Maybank
- Shijie Geng
- Lingxi Xie
Papers from Chenglin Yang's perspective
Ordered by how strongly the researchers Chenglin Yang trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Snapshot Distillation: Teacher-Student Optimization in One Generation (2018) — 238 citations
- Training Deep Neural Networks in Generations: A More Tolerant Teacher Educates Better Students (2018) — 149 citations
- Knowledge Distillation in Generations: More Tolerant Teachers Educate Better Students (2018) — 81 citations