Code for Robustness Distributions in Neural Network Verification

This repository contains the code and models from the paper:
Robustness Distributionsin Neural Network Verification
Author(s): [Your Name(s)]
Published in: [Conference/Journal Name, Year]

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Table of Contents

• Code for Robustness Distributions in Neural Network Verification
  • Table of Contents
  • Overview
  • Repository Structure
  • External Packages

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Overview

This repository provides:

• Pre-trained models in ONNX format.
• PyTorch implementations for training and verification of the models.
• Experimentation scripts and instructions for reproducing results on MNIST, CIFAR-10, and GTSRB datasets.

The aim of this project is to [briefly describe the main objective/purpose of your research or code].

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Repository Structure

• network_onnx: Network in the onnx formats
  • MNIST
    • mnist_6_256_fgsm.onnx
    • mnist_6_256_pgd.onnx
    • mnist_6_256_standard.onnx
    • mnist_7_1024_fgsm.onnx
    • mnist_7_1024_pgd.onnx
    • mnist_7_1024_standard.onnx
  • CIFAR-10
    • cifar_7_1024_fgsm.onnx
    • cifar_7_1024_pgd.onnx
    • cifar_7_1024_standard.onnx
    • conv_big_fgsm.onnx
    • conv_big_pgd.onnx
    • conv_big_standard.onnx
    • resnet_4b_fgsm.onnx
    • resnet_4b_pgd.onnx
    • resnet_4b_standard.onnx
  • GTSRB
    • gtsrb_6_256_fgsm.onnx
    • gtsrb_6_256_pgd.onnx
    • gtsrb_6_256_standard.onnx
    • gtsrb_7_1024_fgsm.onnx
    • gtsrb_7_1024_pgd.onnx
    • gtsrb_7_1024_standard.onnx
• training: Code for the training and PyTorch implementations for the networks
• verification: Code for verifying the networks

External Packages

This project uses the following external packages:

• VERONA: An open-source package for creating Robustness Distributions.
• adversarial-training-box: An open-source package for adversarial training of neural networks with PyTorch.