Nicolas Papernot
Publications by Year
Research Areas
Adversarial Robustness in Machine Learning, Privacy-Preserving Technologies in Data, Anomaly Detection Techniques and Applications, Advanced Malware Detection Techniques, Cryptography and Data Security
Most-Cited Works
- → The Limitations of Deep Learning in Adversarial Settings(2016)3,867 cited
- → Practical Black-Box Attacks against Machine Learning(2017)3,417 cited
- Ensemble Adversarial Training: Attacks and Defenses(2017)
- → Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples(2016)1,415 cited
- → MixMatch: A Holistic Approach to Semi-Supervised Learning(2019)604 cited
- → On Evaluating Adversarial Robustness(2019)580 cited
- → Adversarial Examples for Malware Detection(2017)543 cited
- → Machine Unlearning(2021)524 cited
- SoK: Towards the Science of security and privacy in machine learning(2018)