Michael Moore

Artificial Intelligence · 2018

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Safety, Robustness & Interpretability — 21 citations into it
• Signal Processing — 8 citations into it
• Computer Networks and Communications — 5 citations into it

Whom Michael Moore trusts overall

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

1. Battista Biggio
2. Blaine Nelson
3. Nicolas Papernot
4. Bernhard Schölkopf
5. Ian J. Goodfellow

Papers from Michael Moore's perspective

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

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

Their papers

• Attack Strength vs. Detectability Dilemma in Adversarial Machine Learning (2018) — 36 citations