Junfeng Yang
Artificial Intelligence · with Cao · 2015–2018
A researcher in the Science corpus: 6 papers; trusts 227 researchers and is trusted by 80 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 143 citations into it; #3,563 of 35,345 by trust here, #5,002 by citations
- Safety, Robustness & Interpretability — 115 citations into it; #489 of 2,251 by trust here, #641 by citations
- Computer Vision and Pattern Recognition — 70 citations into it
- Signal Processing — 46 citations into it; #1,830 of 7,572 by trust here, #1,170 by citations
- Computer Networks and Communications — 32 citations into it
- Privacy & Security — 28 citations into it; #110 of 709 by trust here, #318 by citations
- Information Systems — 23 citations into it
- Software — 19 citations into it; #1,206 of 1,227 by trust here, #602 by citations
Whom Junfeng Yang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Christian Szegedy
- Geoffrey E. Hinton
- Alex Krizhevsky
- Ian J. Goodfellow
- Kaiming He
- Yann LeCun
- Karen Simonyan
- Jia Deng
- Yoshua Bengio
- Ilya Sutskever
Who trusts Junfeng Yang overall
- Shiqi Wang
- Tianwei Zhang
- Zecheng He
- Kexin Pei
- Lei Ma
- Meghdad Kurmanji
- Thomas Baumhauer
- Yinjun Wu
- Quoc Phong Nguyen
- Yinzhi Cao
Papers from Junfeng Yang's perspective
Ordered by how strongly the researchers Junfeng Yang 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)
- 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)
- 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
- Towards Making Systems Forget with Machine Unlearning (2015) — 1,123 citations
- DeepXplore: Automated Whitebox Testing of Deep Learning Systems (2017) — 1,541 citations
- Formal Security Analysis of Neural Networks using Symbolic Intervals (2018) — 532 citations
- Efficient Formal Safety Analysis of Neural Networks (2018) — 458 citations
- Efficient Repair of Polluted Machine Learning Systems via Causal Unlearning (2018) — 55 citations
- Towards Practical Verification of Machine Learning: The Case of Computer Vision Systems (2017) — 108 citations