Weilin Xu

Artificial Intelligence · with Evans · 2016–2017

A researcher in the Science corpus: 4 papers; trusts 69 researchers and is trusted by 71 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 49 citations into it; #5,729 of 35,345 by trust here, #6,614 by citations
• Safety, Robustness & Interpretability — 49 citations into it; #243 of 2,251 by trust here, #419 by citations
• Computer Vision and Pattern Recognition — 22 citations into it
• Signal Processing — 22 citations into it; #2,103 of 7,572 by trust here, #2,052 by citations
• Computer Networks and Communications — 13 citations into it; #2,387 of 9,886 by trust here, #3,074 by citations
• Information Systems — 11 citations into it; #2,050 of 8,771 by trust here, #2,741 by citations
• Privacy & Security — 8 citations into it; #292 of 709 by trust here, #420 by citations

Whom Weilin Xu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Nicolas Papernot
2. Alex Krizhevsky
3. Ian J. Goodfellow
4. Yann LeCun
5. Geoffrey E. Hinton
6. Christian Szegedy
7. Nedim Srndic
8. Patrick Drew McDaniel
9. Yoshua Bengio
10. Ilya Sutskever

Who trusts Weilin Xu overall

1. Nicolas Papernot
2. Kui Ren
3. Yisen Wang
4. Liang Tong
5. Shashank Kotyan
6. Danilo Vasconcellos Vargas
7. Yingqi Liu
8. Jamie Hayes
9. Bo Li
10. Davide Maiorca

Papers from Weilin Xu's perspective

Ordered by how strongly the researchers Weilin Xu trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Learning Multiple Layers of Features from Tiny Images
8. Attention is All you Need (Neural Information Processing Systems)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks (2017) — 1,705 citations
• Feature Squeezing Mitigates and Detects Carlini/Wagner Adversarial Examples (2017) — 47 citations
• Security Risks in Deep Learning Implementations (2017) — 85 citations
• Automatically Evading Classifiers: A Case Study on PDF Malware Classifiers (2016) — 249 citations