/Papers-of-Robust-ML

Related papers for robust machine learning

Papers-of-Robust-ML

Related papers for robust machine learning (we mainly focus on defenses).

Statement

Since there are tens of new papers on adversarial defense in each conference, we are only able to update those we just read and consider as insightful.

Anyone is welcomed to submit a pull request for the related and unlisted papers on adversarial defense, which are pulished on peer-review conferences (ICML/NeurIPS/ICLR/CVPR etc.) or released on arXiv.

Contents

General Defenses (training phase)

General Defenses (inference phase)

Adversarial Detection

Certified Defense and Model Verification

Theoretical Analysis

Empirical Analysis

Beyond Safety

Seminal Work

Benchmark Datasets