A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

A Python library for Secure and Explainable Machine Learning

Foolbox implementation for NeurIPS 2021 Paper: "Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints".

No description available

Framework for the Adversarial Machine Learning Challenge at CU Denver, showcasing techniques in AI model defense and attack.

Toolbox for manipulating functions

Foolbox Native brings native performance to Foolbox

Notes on using the Brendel & Bethge attack with Foolbox and Cleverhans

The unofficial chinese document of foolbox.

Generating adversarial avatars for m3inference with PyTorch and Foolbox

A graphical tool to test the robustness of classifiers using Foolbox.

Foolbox Attacks

my javascript foolbox

The pretrained TensorFlow Keras models with a Foolbox Zoo compatible interface

financial toolbox

Modifying bits of foolbox to work for particular BindsNET experiments.

foolbox for ManifoldCAD js

tutorail_pytorch_foolbox

Foolbox wrapper for robustbench models.

My custom FYP foolbox implementation

No description available

A sandbox for fooling around with rust.

Adversarial Attacks on Resnet18 with Foolbox

No description available

No description available

Foolbox model zoo implementation of a pretrained ResNet-50 v2 with logit pairing

This repository investigates the impact of adversarial attacks on the explainability of Deep Neural Networks, specifically focusing on Saliency Map explanations.

Malware classifier practice and paper revision from security subject. ML and BD master degree from UPM.

A conda-smithy repository for foolbox.

My custom FYP foolbox implementation