awesome-explainable-graph-reasoning VS AIX360

Compare awesome-explainable-graph-reasoning vs AIX360 and see what are their differences.

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awesome-explainable-graph-reasoning AIX360
1 2
1,934 1,533
0.3% 3.1%
0.0 8.2
about 2 years ago about 2 months ago
Python
Apache License 2.0 Apache License 2.0
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.

awesome-explainable-graph-reasoning

Posts with mentions or reviews of awesome-explainable-graph-reasoning. We have used some of these posts to build our list of alternatives and similar projects.

AIX360

Posts with mentions or reviews of AIX360. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-10-28.

What are some alternatives?

When comparing awesome-explainable-graph-reasoning and AIX360 you can also consider the following projects:

awesome-project-ideas - Curated list of Machine Learning, NLP, Vision, Recommender Systems Project Ideas

AIF360 - A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

explainable-cnn - 📦 PyTorch based visualization package for generating layer-wise explanations for CNNs.

cleverhans - An adversarial example library for constructing attacks, building defenses, and benchmarking both

DiCE - Generate Diverse Counterfactual Explanations for any machine learning model.

awesome-shapley-value - Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)

backpack - BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.

DALEX - moDel Agnostic Language for Exploration and eXplanation

TorchDrift - Drift Detection for your PyTorch Models

pytea - PyTea: PyTorch Tensor shape error analyzer

shapash - 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

shapley - The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).