Jia Wu
Computer Vision and Pattern Recognition · with Chen · 2017–2020
A researcher in the Science corpus: 3 papers; trusts 64 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 67 citations into it; #13,813 of 21,575 by trust here, #11,083 by citations
- Artificial Intelligence — 25 citations into it
- Representation & Self-Supervised Learning — 12 citations into it
- Information Systems — 8 citations into it
- Optimization & Training — 7 citations into it
Whom Jia Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Alex Krizhevsky
- Geoffrey E. Hinton
- Yann LeCun
- Yoshua Bengio
- Adam Coates
- Andrew Y. Ng
- Kaiming He
- Ilya Sutskever
- Diederik P. Kingma
- Rob Fergus
Who trusts Jia Wu overall
Papers from Jia Wu's perspective
Ordered by how strongly the researchers Jia Wu 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)
- Gradient-based learning applied to document recognition
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
- 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)
- Going deeper with convolutions
Their papers
- Infrared and visible image fusion via detail preserving adversarial learning (2020) — 420 citations
- A Deep Framework for Cross-Domain and Cross-System Recommendations (2018) — 177 citations
- Stacked Convolutional Denoising Auto-Encoders for Feature Representation (2017) — 390 citations