A tic-tac-toe using minmax adversial search algorithm as an opponent
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Updated
Apr 18, 2021 - Python
A tic-tac-toe using minmax adversial search algorithm as an opponent
AROID: Improving Adversarial Robustness Through Online Instance-Wise Data Augmentation. IJCV 2024.
A New Context-Aware Framework for Defending Against Adversarial Attacks in Hyperspectral Image Classification (IEEE TGRS 2023)
Defending Neural Networks from Adversarial Attacks
Framework for creating Adversarial Attacks on Deep Neural Networks with Evolutionary Strategies (ES).
Framework for generating Adversarial Attacks on Deep Neural Networks using Evolutionary Strategies (ES).
An unofficial version of the PyTorch implementation of CURE and Fast Adversarial training with FGSM.
[UAI 2024 paper] DistriBlock: Identifying adversarial audio samples by leveraging characteristics of the output distribution.
Recognition by Components
Source of the ECCV22 paper "LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity"
Explanation-guided boosting of machine learning evasion attacks.
A reproduced version of PyTorch from the official repository, based on TensorFlow/JAX.
A brief study on Adversarial Attacks and python scripts to generate and study them.
A Python toolbox to create adversarial examples that fool neural networks in PyTorch.
iax, is a library created to simplify the search of adversarial examples within a masked area of an image in a black-box scenario. currently implemented with a PSO search algorithm.
[ECCV 2020 AROW Workshop] A Deep Dive into Adversarial Robustness in Zero-Shot Learning
Source code for ESORICS 2020 paper "Detection by attack: Detecting adversarial samples by undercover attack"
experimenting effects of adversarial patch attacks to some of targets on python (pytorch)
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