Zhuxi Jiang
Computer Vision and Pattern Recognition · 2016–2018
A researcher in the Science corpus: 2 papers; trusts 55 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 36 citations into it
- Artificial Intelligence — 23 citations into it
- Generative Models — 15 citations into it
- Representation & Self-Supervised Learning — 12 citations into it
Whom Zhuxi Jiang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yann LeCun
- Yoshua Bengio
- Kaiming He
- Alex Krizhevsky
- Andrew Y. Ng
- Ilya Sutskever
- Max Welling
- Radford M. Neal
Who trusts Zhuxi Jiang overall
- Lyle Regenwetter
- Tingting Zhao
- Xu Yang
- Dushyant Rao
- Deyu Bo
- Wei-Ning Hsu
- Amin Heyrani Nobari
- Zifeng Wang
Papers from Zhuxi Jiang's perspective
Ordered by how strongly the researchers Zhuxi Jiang 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
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Variational Deep Embedding: An Unsupervised and Generative Approach to Clustering (2016) — 869 citations
- A hybrid deep learning based traffic flow prediction method and its understanding (2018) — 698 citations