Matthew Wicker

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 21 researchers and is trusted by 9 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it; #14,328 of 35,345 by trust here, #21,316 by citations
• Safety, Robustness & Interpretability — 20 citations into it
• Computer Vision and Pattern Recognition — 15 citations into it; #9,310 of 21,575 by trust here, #14,151 by citations

Whom Matthew Wicker trusts overall

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

1. Xiaowei Huang
2. David G. Lowe
3. Ian J. Goodfellow
4. Christian Szegedy
5. Nicolas Papernot
6. Douglas A. Reynolds
7. Yann LeCun
8. Nicholas Carlini
9. Geoffrey E. Hinton
10. Guy Katz

Who trusts Matthew Wicker overall

1. Wenjie Ruan
2. Augustus Odena
3. Xiaowei Huang
4. Youcheng Sun
5. Jie M. Zhang
6. Jianmin Guo
7. Min Wu
8. Lei Ma
9. Xingyu Zhao
10. Marta Z. Kwiatkowska

Papers from Matthew Wicker's perspective

Ordered by how strongly the researchers Matthew Wicker 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. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Feature-Guided Black-Box Safety Testing of Deep Neural Networks (2017) — 247 citations