Felix Juefei-Xu
Computer Vision and Pattern Recognition · 2018–2019
A researcher in the Science corpus: 5 papers; trusts 169 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 107 citations into it
- Artificial Intelligence — 86 citations into it
- Safety, Robustness & Interpretability — 59 citations into it
- Generative Models — 35 citations into it
- Signal Processing — 23 citations into it
- Optimization & Training — 9 citations into it
- Model Architectures — 7 citations into it
Whom Felix Juefei-Xu trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Yann LeCun
- Geoffrey E. Hinton
- Yoshua Bengio
- Alex Krizhevsky
- Ian J. Goodfellow
- Karen Simonyan
- Kaiming He
- Ilya Sutskever
- Andrew Zisserman
Who trusts Felix Juefei-Xu overall
Papers from Felix Juefei-Xu's perspective
Ordered by how strongly the researchers Felix Juefei-Xu 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
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- 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
- FakeSpotter: A Simple Baseline for Spotting AI-Synthesized Fake Faces (2019) — 60 citations
- RankGAN: A Maximum Margin Ranking GAN for Generating Faces (2018) — 24 citations
- DeepMutation: Mutation Testing of Deep Learning Systems (2018) — 401 citations
- DeepHunter: a coverage-guided fuzz testing framework for deep neural networks (2019) — 472 citations
- DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems (2018) — 708 citations