adversarial-robustness-toolbox VS Differential-Privacy-Guide

Compare adversarial-robustness-toolbox vs Differential-Privacy-Guide and see what are their differences.

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adversarial-robustness-toolbox Differential-Privacy-Guide
8 1
4,460 13
2.9% -
9.7 2.6
6 days ago over 2 years ago
Python Python
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

adversarial-robustness-toolbox

Posts with mentions or reviews of adversarial-robustness-toolbox. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-01-22.

Differential-Privacy-Guide

Posts with mentions or reviews of Differential-Privacy-Guide. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing adversarial-robustness-toolbox and Differential-Privacy-Guide you can also consider the following projects:

DeepRobust - A pytorch adversarial library for attack and defense methods on images and graphs

tf-encrypted - A Framework for Encrypted Machine Learning in TensorFlow

auto-attack - Code relative to "Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks"

gretel-python-client - The Gretel Python Client allows you to interact with the Gretel REST API.

TextAttack - TextAttack 🐙 is a Python framework for adversarial attacks, data augmentation, and model training in NLP https://textattack.readthedocs.io/en/master/

ReTube - ReImagine Tubing

alpha-zero-boosted - A "build to learn" Alpha Zero implementation using Gradient Boosted Decision Trees (LightGBM)

privacy - Library for training machine learning models with privacy for training data

m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies

isp-data-pollution - ISP Data Pollution to Protect Private Browsing History with Obfuscation

waf-bypass - Check your WAF before an attacker does

gretel-synthetics - Synthetic data generators for structured and unstructured text, featuring differentially private learning.