Jiqing Wu
Computer Vision and Pattern Recognition · 2016–2018
A researcher in the Science corpus: 3 papers; trusts 426 researchers and is trusted by 11 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 70 citations into it; #9,934 of 21,575 by trust here, #10,500 by citations
- Artificial Intelligence — 30 citations into it
- Generative Models — 30 citations into it
- Media Technology — 21 citations into it
- Optimization & Training — 13 citations into it
- Model Architectures — 12 citations into it
- Computational Mechanics — 7 citations into it; #7,887 of 10,001 by trust here, #9,276 by citations
- Evaluation & Benchmarks — 6 citations into it
Whom Jiqing Wu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- L. Eon Bottou
- Yann LeCun
- Sergey Ioffe
- Christian Szegedy
- Jimmy Ba
Who trusts Jiqing Wu overall
Papers from Jiqing Wu's perspective
Ordered by how strongly the researchers Jiqing Wu 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
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- NTIRE 2018 Challenge on Single Image Super-Resolution: Methods and Results (2018) — 354 citations
- Wasserstein Divergence for GANs (2017) — 163 citations
- Building Deep Networks on Grassmann Manifolds (2016) — 198 citations