Alexander Levine

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 24 citations into it
• Safety, Robustness & Interpretability — 22 citations into it

Whom Alexander Levine trusts overall

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

1. Ian J. Goodfellow
2. Amirata Ghorbani
3. Aleksander Madry
4. Christian Szegedy
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Daniel Smilkov
8. Mathias Lécuyer
9. Karen Simonyan
10. Jérôme Rony

Papers from Alexander Levine's perspective

Ordered by how strongly the researchers Alexander Levine 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. Gradient-based learning applied to document recognition
4. ImageNet: A large-scale hierarchical image database
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Certifiably Robust Interpretation in Deep Learning (2019) — 65 citations