Justin Lewis

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 22 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 26 citations into it
• Safety, Robustness & Interpretability — 24 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Electrical and Electronic Engineering — 7 citations into it

Whom Justin Lewis trusts overall

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

1. Christian Szegedy
2. Ian J. Goodfellow
3. Matthias Hein
4. Alessio R. Lomuscio
5. Matteo Fischetti
6. Kevin Scaman
7. Vincent Tjeng
8. Chih-Hong Cheng
9. Yusuke Tsuzuku
10. Geoffrey E. Hinton

Papers from Justin Lewis's perspective

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

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

Their papers

• Provable Certificates for Adversarial Examples: Fitting a Ball in the Union of Polytopes (2019) — 61 citations