Provable Adversarial Defense

3 papers with code • 2 benchmarks • 2 datasets

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Most implemented papers

Certified Defense to Image Transformations via Randomized Smoothing

eth-sri/transformation-smoothing NeurIPS 2020

We extend randomized smoothing to cover parameterized transformations (e. g., rotations, translations) and certify robustness in the parameter space (e. g., rotation angle).

Towards Adversarial Patch Analysis and Certified Defense against Crowd Counting

harrywuhust2022/Adv-Crowd-analysis 22 Apr 2021

Crowd counting has drawn much attention due to its importance in safety-critical surveillance systems.

A Unified Algebraic Perspective on Lipschitz Neural Networks

araujoalexandre/lipschitz-sll-networks ICLR 2023

Important research efforts have focused on the design and training of neural networks with a controlled Lipschitz constant.