Maura Pintor

Safety, Robustness & Interpretability · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Safety, Robustness & Interpretability — 57 citations into it
• Artificial Intelligence — 55 citations into it
• Signal Processing — 27 citations into it
• Computer Networks and Communications — 15 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it
• Information Systems — 8 citations into it
• Molecular Biology — 5 citations into it

Whom Maura Pintor trusts overall

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

1. Battista Biggio
2. Ambra Demontis
3. Blaine Nelson
4. Nicholas Carlini
5. Fabio Roli
6. Pang Wei Koh
7. Christian Szegedy
8. Ian J. Goodfellow
9. Marco Barreno
10. Geoffrey E. Hinton

Who trusts Maura Pintor overall

1. Davide Maiorca

Papers from Maura Pintor's perspective

Ordered by how strongly the researchers Maura Pintor 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. Gradient-based learning applied to document recognition
4. Intriguing properties of neural networks
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. Long Short-Term Memory
9. Learning Multiple Layers of Features from Tiny Images
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• secml: A Python Library for Secure and Explainable Machine Learning (2019) — 42 citations
• Why Do Adversarial Attacks Transfer? Explaining Transferability of Evasion and Poisoning Attacks (2018) — 477 citations