explainable-artificial-intelligence

There are 170 repositories under explainable-artificial-intelligence topic.

  • DALEX

    ModelOriented/DALEX

    moDel Agnostic Language for Exploration and eXplanation

    Language:Python1.4k50408169
  • explainx

    explainX/explainx

    Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms8909@nyu.edu

    Language:Jupyter Notebook43993156
  • pyss3

    sergioburdisso/pyss3

    A Python library for Interpretable Machine Learning in Text Classification using the SS3 model, with easy-to-use visualization tools for Explainable AI :octocat:

    Language:Python344192244

  • adityac94/Grad_CAM_plus_plus

    A generalized gradient-based CNN visualization technique

    Language:Python28991556
  • awesome-shapley-value

    AstraZeneca/awesome-shapley-value

    Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)

    1531012

  • fzi-forschungszentrum-informatik/TSInterpret

    An Open-Source Library for the interpretability of time series classifiers

    Language:Python14133813

  • ajayarunachalam/msda

    Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector

    Language:Jupyter Notebook1299330

  • dylan-slack/TalkToModel

    TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!

    Language:Python1245627

  • andreysharapov/xaience

    All about explainable AI, algorithmic fairness and more

    Language:HTML1109013

  • fitushar/3D-GuidedGradCAM-for-Medical-Imaging

    This Repo containes the implemnetation of generating Guided-GradCAM for 3D medical Imaging using Nifti file in tensorflow 2.0. Different input files can be used in that case need to edit the input to the Guided-gradCAM model.

    Language:Python105167

  • emanuel-metzenthin/Lime-For-Time

    Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification

    Language:Python966921

  • ModelOriented/treeshap

    Compute SHAP values for your tree-based models using the TreeSHAP algorithm

    Language:R89132824

  • zju-vipa/awesome-neural-trees

    Introduction, selected papers and possible corresponding codes in our review paper "A Survey of Neural Trees"

    83309

  • rehmanzafar/xai-iml-sota

    Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.

    Language:R746017

  • M-Nauta/PIPNet

    PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)

    Language:Python711831

  • greydanus/excitationbp

    Visualizing how deep networks make decisions

    Language:Jupyter Notebook666922

  • ModelOriented/auditor

    Model verification, validation, and error analysis

    Language:R58199413
  • xai_thyroid

    hungntt/xai_thyroid

    Classification and Object Detection XAI methods (CAM-based, backpropagation-based, perturbation-based, statistic-based) for thyroid cancer ultrasound images

    Language:Python53238
  • dianna

    dianna-ai/dianna

    Deep Insight And Neural Network Analysis

    Language:Jupyter Notebook52455312

  • akarasman/yolo-heatmaps

    A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).

    Language:Jupyter Notebook5111313

  • koulanurag/mmn

    Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks

    Language:Python514313

  • yaricom/goNEAT_NS

    This project provides GOLang implementation of Neuro-Evolution of Augmenting Topologies (NEAT) with Novelty Search optimization aimed to solve deceptive tasks with strong local optima

    Language:Go42507

  • koo-ec/Awesome-LLM-Explainability

    A curated list of explainability-related papers, articles, and resources focused on Large Language Models (LLMs). This repository aims to provide researchers, practitioners, and enthusiasts with insights into the explainability implications, challenges, and advancements surrounding these powerful models.

    41201

  • zju-vipa/ProtoPFormer

    ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition

    Language:Python373511

  • xmq1221/awesome-prototype-based-papers

    This is a list of awesome prototype-based papers for explainable artificial intelligence.

    36101

  • shrebox/B-cosification

    [NeurIPS 2024] Code for the paper: B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable.

    Language:Jupyter Notebook33410

  • dbountouridis/siren

    SIREN: A Simulation Framework for Understanding the Effects of Recommender Systems in Online News Environments

    Language:Python29138

  • KaryFramling/py-ciu

    Explainable Artificial Intelligence through Contextual Importance and Utility

    Language:Jupyter Notebook28488

  • cair/fast-tsetlin-machine-in-cuda-with-imdb-demo

    A CUDA implementation of the Tsetlin Machine based on bitwise operators

    Language:Cuda26812

  • xai4se/xai4se.github.io

    Explainable AI for Software Engineering: A Hands-on Guide on How to Make Software Analytics More Practical, Explainable, and Actionable (https://xai4se.github.io)

    Language:Shell25109

  • imatge-upc/SurvLIMEpy

    Local interpretability for survival models

    Language:Python24524
  • ATgfe

    ahmed-mohamed-sn/ATgfe

    Automated Transparent Genetic Feature Engineering

    22715

  • declare-lab/identifiable-transformers

    Language:Python22322
  • Arena

    ModelOriented/Arena

    Interactive XAI dashboard

    Language:Vue22342

  • yuntech-bdrc/WaterQuality

    An explainable water quality classification model

    Language:Jupyter Notebook21102

  • alonjacovi/XAI-Scholar

    Cross-field empirical trends analysis of XAI literature

    Language:Jupyter Notebook20115