Yubei Chen
Computer Vision and Pattern Recognition · 2019–2021
A researcher in the Science corpus: 4 papers; trusts 404 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 106 citations into it; #16,869 of 21,575 by trust here, #12,172 by citations
- Artificial Intelligence — 93 citations into it; #27,660 of 35,345 by trust here, #18,186 by citations
- Representation & Self-Supervised Learning — 49 citations into it
- Generative Models — 45 citations into it; #1,553 of 1,956 by trust here, #1,635 by citations
- Probabilistic & Bayesian Methods — 40 citations into it; #1,282 of 1,525 by trust here, #1,136 by citations
- Optimization & Training — 17 citations into it
- Signal Processing — 17 citations into it
- Model Architectures — 14 citations into it
Whom Yubei Chen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Alex Krizhevsky
- Kaiming He
- Diederik P. Kingma
- Radford M. Neal
- Yoshua Bengio
- Yann LeCun
- Ruslan Salakhutdinov
- Ilya Sutskever
- Pascal Vincent
Who trusts Yubei Chen overall
Papers from Yubei Chen's perspective
Ordered by how strongly the researchers Yubei Chen 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)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Superposition of many models into one (2019) — 127 citations
- Decoupled Contrastive Learning (2021) — 259 citations
- Learning Energy-Based Models in High-Dimensional Spaces with Multiscale Denoising-Score Matching (2019) — 34 citations
- Annealed Denoising Score Matching: Learning Energy-Based Models in High-Dimensional Spaces (2019) — 13 citations