21 Repositories
Python xai Libraries
Official Code Implementation of the paper : XAI for Transformers: Better Explanations through Conservative Propagation
Official Code Implementation of The Paper : XAI for Transformers: Better Explanations through Conservative Propagation For the SST-2 and IMDB expermin
EXplainable Artificial Intelligence (XAI)
EXplainable Artificial Intelligence (XAI) This repository includes the codes for different projects on eXplainable Artificial Intelligence (XAI) by th
Final term project for Bayesian Machine Learning Lecture (XAI-623)
Mixquality_AL Final Term Project For Bayesian Machine Learning Lecture (XAI-623) Youtube Link The presentation is given in YoutubeLink Problem Formula
Papers about explainability of GNNs
Papers about explainability of GNNs
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification".
Rule-based Representation Learner This is a PyTorch implementation of Rule-based Representation Learner (RRL) as described in NeurIPS 2021 paper: Scal
Scrutinizing XAI with linear ground-truth data
This repository contains all the experiments presented in the corresponding paper: "Scrutinizing XAI using linear ground-truth data with suppressor va
Responsible Machine Learning with Python
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
DrWhy is the collection of tools for eXplainable AI (XAI). It's based on shared principles and simple grammar for exploration, explanation and visualisation of predictive models.
Responsible Machine Learning With Great Power Comes Great Responsibility. Voltaire (well, maybe) How to develop machine learning models in a responsib
XAI - An eXplainability toolbox for machine learning
XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai
moDel Agnostic Language for Exploration and eXplanation
moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.
Fit interpretable models. Explain blackbox machine learning.
InterpretML - Alpha Release In the beginning machines learned in darkness, and data scientists struggled in the void to explain them. Let there be lig
A diff tool for language models
LMdiff Qualitative comparison of large language models. Demo & Paper: http://lmdiff.net LMdiff is a MIT-IBM Watson AI Lab collaboration between: Hendr
Adaptive, interpretable wavelets across domains (NeurIPS 2021)
Adaptive wavelets Wavelets which adapt given data (and optionally a pre-trained model). This yields models which are faster, more compressible, and mo
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
GNNLens2 is an interactive visualization tool for graph neural networks (GNN).
👋🦊 Xplique is a Python toolkit dedicated to explainability, currently based on Tensorflow.
👋🦊 Xplique is a Python toolkit dedicated to explainability, currently based on Tensorflow.
Code for CVPR2021 "Visualizing Adapted Knowledge in Domain Transfer". Visualization for domain adaptation. #explainable-ai
Visualizing Adapted Knowledge in Domain Transfer @inproceedings{hou2021visualizing, title={Visualizing Adapted Knowledge in Domain Transfer}, auth
Interpretability and explainability of data and machine learning models
AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase
Algorithms for monitoring and explaining machine learning models
Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-qual
Predictive AI layer for existing databases.
MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning
A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:
A Python package implementing a new model for text classification with visualization tools for Explainable AI 🍣 Online live demos: http://tworld.io/s
Predictive AI layer for existing databases.
MindsDB is an open-source AI layer for existing databases that allows you to effortlessly develop, train and deploy state-of-the-art machine learning