GitHub topics: explainable-ai

Repositories

sametcopur/ruleopt

Optimization-Based Rule Learning for Classification

Language: Python - Size: 225 KB - Last synced at: about 7 hours ago - Pushed at: about 8 hours ago - Stars: 47 - Forks: 1

FarnoushRJ/SymbolicXAI

Official Implementation of the Paper "Towards symbolic XAI – explanation through human understandable logical relationships between features"

Language: Jupyter Notebook - Size: 19.2 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 0 - Forks: 0

Fuminides/ex-fuzzy

A Python library for explainable AI using approximate reasoning

Language: Python - Size: 13.8 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 26 - Forks: 6

pradippramanick/coexp-iros24

Code and data for the IROS 2024 paper - Multimodal Coherent Explanation Generation of Robot Failures

Language: Python - Size: 1.01 MB - Last synced at: 1 day ago - Pushed at: 1 day ago - Stars: 1 - Forks: 0

trustyai-explainability/trustyai-explainability.github.io

TrustyAI main documentation

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The first prototype for a Clear-glass Gen-AI development project in its infancy. Its focus is to be wholly user-centric, privacy conscious, and completely original. All while using white-box or transparent development processes and explainable logic.

Language: CSS - Size: 7.81 KB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 0 - Forks: 0

devendew/YOLOv8-based-indoor-fire-and-smoke-detection

Explainable AI and YOLOv8-based Framework for Indoor Fire and Smoke Detection

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microsoft/responsible-ai-toolbox

Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.

Language: TypeScript - Size: 111 MB - Last synced at: 2 days ago - Pushed at: 4 months ago - Stars: 1,552 - Forks: 409

interpretml/interpret

Fit interpretable models. Explain blackbox machine learning.

Language: C++ - Size: 14.8 MB - Last synced at: 2 days ago - Pushed at: 3 days ago - Stars: 6,516 - Forks: 749

Cuonghoangit/GeoMineralInsight

This project uses machine learning to analyze geological, geochemical, aeromagnetic, and remote sensing data over 39,000 sq. km in southern India. It identifies high-probability zones for concealed Au, Cu, and PGE deposits using XGBoost, SHAP, and GeoPandas. Key features include automated pipelines, explainable AI, and GIS-ready maps.

Language: Jupyter Notebook - Size: 7.38 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 0 - Forks: 0

evanseitz/squid-nn

surrogate quantitative interpretability for deepnets

Language: Python - Size: 3.82 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 21 - Forks: 1

KaryFramling/ciu

R implementation of Contextual Importance and Utility for Explainable AI

Language: R - Size: 6.33 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 10 - Forks: 5

guidogagl/physioex

PhysioEx, a PyTorch Lightning based library for Interpretable physiological signal classifiers

Language: Python - Size: 113 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 17 - Forks: 8

HelmholtzAI-Consultants-Munich/fg-clustering

Explainability for Random Forest Models.

Language: Jupyter Notebook - Size: 31.4 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 27 - Forks: 10

AslanDing/Robust-Fidelity

a robust metric (robust fidelity) for XGNN (ICLR24)

Language: Python - Size: 3.49 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 8 - Forks: 0

fixouttech/fixout

Algorithmic inspection for trustworthy ML models

Language: Python - Size: 10.7 MB - Last synced at: about 21 hours ago - Pushed at: about 1 month ago - Stars: 4 - Forks: 0

SirBleu/Intelligent-Analytics-Artificial-Neural-Networks

This repository contains my work and learnings from a class on Intelligent Analytics. It contains works on Percetrons, Support Vector Machines, Deep Learning methods, Dimensionality Reduction, Decision Trees, Ensemble methods and so much more. It's for my continous learning on the subject

Size: 1.95 KB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 1 - Forks: 0

dubprime/mythral

Mythral Neurosymbolic AI

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RuoyuChen10/SMDL-Attribution

[ICLR 2024 Oral] Less is More: Fewer Interpretable Region via Submodular Subset Selection

Language: Jupyter Notebook - Size: 28.9 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 77 - Forks: 4

VincentGranville/Machine-Learning

Material related to my book Intuitive Machine Learning. Some of this material is also featured in my new book Synthetic Data and Generative AI.

Language: Python - Size: 36.2 MB - Last synced at: 4 days ago - Pushed at: 4 days ago - Stars: 112 - Forks: 34

JoaoLages/diffusers-interpret

Diffusers-Interpret 🤗🧨🕵️‍♀️: Model explainability for 🤗 Diffusers. Get explanations for your generated images.

Language: Jupyter Notebook - Size: 77.5 MB - Last synced at: 4 days ago - Pushed at: over 2 years ago - Stars: 277 - Forks: 14

NorskRegnesentral/shapr

Explaining the output of machine learning models with more accurately estimated Shapley values

Language: HTML - Size: 105 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 160 - Forks: 36

csinva/imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Language: Jupyter Notebook - Size: 162 MB - Last synced at: 6 days ago - Pushed at: 3 months ago - Stars: 1,465 - Forks: 124

SKT1803/ai-explanation-tool-grid-explainer

Visual AI explanation tool using grid-based occlusion for CNN interpretability.

Language: Jupyter Notebook - Size: 5.31 MB - Last synced at: 6 days ago - Pushed at: 7 days ago - Stars: 0 - Forks: 0

interpretml/DiCE

Generate Diverse Counterfactual Explanations for any machine learning model.

Language: Python - Size: 14.9 MB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 1,405 - Forks: 203

raktim-mondol/GRAPHITE

State-of-the-art deep learning framework for breast cancer histopathology analysis combining graph-based representations with interpretable AI techniques for enhanced diagnostic insights and clinical decision support.

Language: Python - Size: 223 KB - Last synced at: 7 days ago - Pushed at: 7 days ago - Stars: 0 - Forks: 0

angrysky56/emotion_ai

Adaptive Reflective Companion – or Aura

Language: Python - Size: 1.19 MB - Last synced at: 7 days ago - Pushed at: 8 days ago - Stars: 1 - Forks: 0

mmschlk/shapiq

Shapley Interactions and Shapley Values for Machine Learning

Language: Python - Size: 309 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 554 - Forks: 35

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.

Size: 764 KB - Last synced at: 7 days ago - Pushed at: 8 days ago - Stars: 33 - Forks: 1

SHI-Yu-Zhe/awesome-agi-cocosci

An awesome & curated list for Artificial General Intelligence, an emerging inter-discipline field that combines artificial intelligence and computational cognitive sciences.

Language: TeX - Size: 3.39 MB - Last synced at: 7 days ago - Pushed at: 8 days ago - Stars: 326 - Forks: 23

amoghj98/SHIRE

This repository contains code associated with SHIRE: Enhancing Sample Efficiency using Human Intuition in Reinforcement Learning (ICRA 2025)

Language: Python - Size: 152 KB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 9 - Forks: 0

kserve/website

User documentation for KServe.

Language: HTML - Size: 123 MB - Last synced at: 6 days ago - Pushed at: 6 days ago - Stars: 106 - Forks: 135

fiddler-labs/fiddler-examples

Language: Jupyter Notebook - Size: 289 MB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 13 - Forks: 2

supriya-manna/dp_x_xai

repo for the paper: Reconciling Privacy and Explainability in High-Stakes: A Systematic Inquiry

Size: 2.93 KB - Last synced at: 8 days ago - Pushed at: 8 days ago - Stars: 0 - Forks: 0

dkavargy/KANVAS

A skill-based job classification framework using Kolmogorov–Arnold Networks (KANs)

Language: Python - Size: 164 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 4 - Forks: 1

unitn-sml/recourse-fare

(Explainable) Algorithmic Recourse with Reinforcement Learning and MCTS (FARE and E-FARE)

Language: Python - Size: 1.86 MB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 3 - Forks: 0

DataSciencePolimi/Visual-TCAV

Official TensorFlow V2 implementation of Visual-TCAV, a novel framework for post-hoc explainability in image classification.

Language: Jupyter Notebook - Size: 9.26 MB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 1 - Forks: 1

miltiadiss/CEID_NE577-5G-Architectures-Technologies-Applications-and-Key-Performance-Indexes

This project involves predicting the downlink bitrate of mobile devices in 5G networks using machine learning (XGBoost Regressor) and deep learning (LSTM model). It includes data preprocessing, training and evaluation of the models, applying explainable AI (XAI) techniques such as SHAP, and optimizing feature selection based on XAI insights.

Language: Jupyter Notebook - Size: 59.7 MB - Last synced at: 8 days ago - Pushed at: 10 days ago - Stars: 2 - Forks: 0

alan-ai/alan-sdk-web

The Self-Coding System for Your App — Alan AI SDK for Web

Size: 42.5 MB - Last synced at: 6 days ago - Pushed at: 16 days ago - Stars: 2,406 - Forks: 93

PathologyDataScience/MuTILs_Panoptic

Amgad M, Salgado R, Cooper LA. A panoptic segmentation approach for tumor-infiltrating lymphocyte assessment: development of the MuTILs model and PanopTILs dataset. medRxiv 2022.01.08.22268814.

Language: Python - Size: 266 KB - Last synced at: 10 days ago - Pushed at: 10 days ago - Stars: 19 - Forks: 4

MilesCranmer/PySR

High-Performance Symbolic Regression in Python and Julia

Language: Python - Size: 5.2 MB - Last synced at: 10 days ago - Pushed at: 17 days ago - Stars: 2,823 - Forks: 254

jurisgpt/GrizlyUDVacator-CaseIntake

Symbolic AI for Legal Due Process – A domain-specific reasoning engine for Unlawful Detainer (Eviction) case triage, focused on default judgment relief under California CCP §§473(b) and 473.5. Unlike generative AI, this system performs formal legal reasoning using Answer Set Programming (Clingo), ensuring mathematically provable/ auditable o/p.

Language: Python - Size: 1.52 MB - Last synced at: 11 days ago - Pushed at: 11 days ago - Stars: 0 - Forks: 0

obss/sahi

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

Language: Python - Size: 102 MB - Last synced at: 10 days ago - Pushed at: 23 days ago - Stars: 4,561 - Forks: 654

understandable-machine-intelligence-lab/Quantus

Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations

Language: Jupyter Notebook - Size: 147 MB - Last synced at: 10 days ago - Pushed at: 4 months ago - Stars: 599 - Forks: 77

Trusted-AI/AIX360

Interpretability and explainability of data and machine learning models

Language: Python - Size: 358 MB - Last synced at: 10 days ago - Pushed at: 3 months ago - Stars: 1,698 - Forks: 312

Trustworthy-ML-Lab/CB-LLMs

[ICLR 25] A novel framework for building intrinsically interpretable LLMs with human-understandable concepts to ensure safety, reliability, transparency, and trustworthiness.

Language: Python - Size: 936 KB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 12 - Forks: 3

arpitamisal/MBTI_Personality_Prediction

Text classification model to predict MBTI personality types using user forum data

Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 0 - Forks: 0

inseq-team/inseq

Interpretability for sequence generation models 🐛 🔍

Language: Python - Size: 7.64 MB - Last synced at: 11 days ago - Pushed at: about 1 month ago - Stars: 419 - Forks: 38

MilesCranmer/SymbolicRegression.jl

Distributed High-Performance Symbolic Regression in Julia

Language: Julia - Size: 7.84 MB - Last synced at: 10 days ago - Pushed at: 12 days ago - Stars: 699 - Forks: 106

SriBalaji2112/Advanced-Techniques-for-Detecting-Anomalies-in-EDR-Logs-for-Cybersecurity-SOC-Analytics

This project focuses on building an AI-driven anomaly detection framework that uses the Isolation Forest algorithm to identify suspicious events in unstructured system log data.

Language: Python - Size: 10.6 MB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 0 - Forks: 0

ictnlp/TruthX

Code for ACL 2024 paper "TruthX: Alleviating Hallucinations by Editing Large Language Models in Truthful Space"

Language: Python - Size: 31.6 MB - Last synced at: 5 days ago - Pushed at: about 1 year ago - Stars: 147 - Forks: 6

JuliaTrustworthyAI/AlgorithmicRecourseDynamics.jl

A Julia package for modelling Algorithmic Recourse Dynamics.

Language: TeX - Size: 214 MB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 6 - Forks: 0

Shuyib/HF_model_preview

Using LLMs in huggingface for sentiment analysis, translation, summarization and extractive question answering

Language: Jupyter Notebook - Size: 155 KB - Last synced at: 12 days ago - Pushed at: 12 days ago - Stars: 0 - Forks: 0

habedi/cogitator

A Python toolkit for chain-of-thought prompting 🐍

Language: Python - Size: 126 KB - Last synced at: 9 days ago - Pushed at: 9 days ago - Stars: 165 - Forks: 4

darkrubiks/AI-Assessment-of-Pain-in-Newborns

Inside this repository you will find the code needed to replicate most of our research findings in Pain Assessment in Newborns with AI, developed and researched by FEI and UNIFESP

Language: Python - Size: 5.23 MB - Last synced at: 3 days ago - Pushed at: 3 days ago - Stars: 3 - Forks: 0

ktjkc/reflextrust

Ever wondered why AI answers change? STRATA uncovers the secret architecture of trust inside LLMs.

Size: 6.02 MB - Last synced at: 13 days ago - Pushed at: 13 days ago - Stars: 2 - Forks: 0

cdpierse/transformers-interpret

Model explainability that works seamlessly with 🤗 transformers. Explain your transformers model in just 2 lines of code.

Language: Jupyter Notebook - Size: 7.87 MB - Last synced at: 10 days ago - Pushed at: almost 2 years ago - Stars: 1,346 - Forks: 99

IDSIA/NewTechnoWar

New Techno War, an IDSIA project in collaboration with Armasuisse.

Language: Jupyter Notebook - Size: 27.5 MB - Last synced at: 7 days ago - Pushed at: over 3 years ago - Stars: 4 - Forks: 0

kexi-bq/embedding-explainer

Interactive editor for text meaning via embedding vector control

Size: 235 MB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 0 - Forks: 0

SagharShafaati/Explainable-Air-Quality-Management

This repository provides the Python code for "Explainable Air Quality Management", featuring federated learning with adaptive aggregation, SHAP-based interpretability, and anomaly detection using PrefixSpan. It enhances AQI prediction accuracy and transparency across IoT sensor networks.

Size: 13.7 KB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 0 - Forks: 0

TaimoorKhan10/AI-Fairness-Explainability-Toolkit

AI Fairness and Explainability Toolkit (AFET) is an open-source project aimed at providing tools and frameworks to assess, visualize, and mitigate bias in machine learning models. It supports multiple ML frameworks and offers a comprehensive suite of metrics and visualization components to enhance model transparency and fairness.

Language: Python - Size: 14.6 KB - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 0 - Forks: 0

capitalone/global-attribution-mapping

GAM (Global Attribution Mapping) explains the landscape of neural network predictions across subpopulations

Language: Python - Size: 3.64 MB - Last synced at: 5 days ago - Pushed at: about 2 months ago - Stars: 34 - Forks: 25

AadiSrivastava05/VERITAS-Verification-and-Explanation-of-Realness-in-Images-for-Transparency-in-AI-Systems

We present VERITAS, a comprehensive framework that not only accurately detects whether an image is AI-generated but also explains why it was classified that way through artifact localization and semantic reasoning. Our architecture couples traditional image classifiers with a novel interpretability pipeline.

Language: Jupyter Notebook - Size: 378 MB - Last synced at: 6 days ago - Pushed at: 14 days ago - Stars: 1 - Forks: 1

DanteTrb/Buffett_Evaluator

ML + SHAP + Streamlit: A Buffett-style stock evaluator built for explainable financial decisions.

Language: Jupyter Notebook - Size: 0 Bytes - Last synced at: 14 days ago - Pushed at: 14 days ago - Stars: 0 - Forks: 0

linkedin/FastTreeSHAP

Fast SHAP value computation for interpreting tree-based models

Language: Python - Size: 152 MB - Last synced at: 10 days ago - Pushed at: almost 2 years ago - Stars: 540 - Forks: 34

salesforce/OmniXAI

OmniXAI: A Library for eXplainable AI

Language: Jupyter Notebook - Size: 64.7 MB - Last synced at: 9 days ago - Pushed at: 11 months ago - Stars: 924 - Forks: 99

Renumics/awesome-open-data-centric-ai

Curated list of open source tooling for data-centric AI on unstructured data.

Size: 572 KB - Last synced at: 14 days ago - Pushed at: over 1 year ago - Stars: 719 - Forks: 35

IntelLabs/causality-lab

Causal discovery algorithms and tools for implementing new ones

Language: Jupyter Notebook - Size: 8.52 MB - Last synced at: 15 days ago - Pushed at: 5 months ago - Stars: 219 - Forks: 29

enrypiff/D-RISE_for_YOLO

Explainable AI

Language: Python - Size: 994 KB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0

albertovalerio/brain-tumor-segmentation-with-explainability

The primary objective of this work is to develop an innovative system capable of providing explainable brain tumor detection.

Language: Jupyter Notebook - Size: 150 MB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 1 - Forks: 0

Aronno1920/AI-Engineering

AI Engineering Bootcamp for Programmers - A 19-module, 18-week immersive study plan designed for programmers looking to master AI engineering through real-world projects, foundational theory, and practical tools.

Language: Python - Size: 24.4 KB - Last synced at: 15 days ago - Pushed at: 15 days ago - Stars: 0 - Forks: 0

dlcjfgmlnasa/NeuroXAI

[ESWA] NeuroXAI: Adaptive, Robust, Explainable Surrogate Framework for Determination of Channel Importance in EEG Application

Language: Python - Size: 862 KB - Last synced at: 9 days ago - Pushed at: 6 months ago - Stars: 23 - Forks: 2

s-marton/SYMPOL

(ICLR 2025) Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization

Language: Python - Size: 746 KB - Last synced at: 11 days ago - Pushed at: 9 months ago - Stars: 19 - Forks: 1

ModelOriented/survex

Explainable Machine Learning in Survival Analysis

Language: R - Size: 309 MB - Last synced at: 10 days ago - Pushed at: 12 months ago - Stars: 112 - Forks: 10

ejml1/Deep-Learning-for-Cancer-Detection

An explainable Convolutional Neural Network to classify single cells from bone marrow smears as part of a BSc Dissertation at the University of St Andrews

Language: Jupyter Notebook - Size: 556 MB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 1 - Forks: 0

microsoft/tensorwatch

Debugging, monitoring and visualization for Python Machine Learning and Data Science

Language: Jupyter Notebook - Size: 21.2 MB - Last synced at: 2 days ago - Pushed at: almost 2 years ago - Stars: 3,442 - Forks: 362

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 @ [email protected]

Language: Jupyter Notebook - Size: 61.3 MB - Last synced at: 15 days ago - Pushed at: 10 months ago - Stars: 436 - Forks: 56

tameTNT/evaluating-xai-remote-sensing

My final year (level 3) self-proposed dissertation project undertaken at Durham University in 2024/25 covering satellite imagery, deep learning, explainable AI (xAI), and evaluation metrics for xAI. Submitted to ECAI2025.

Language: Jupyter Notebook - Size: 170 MB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 0 - Forks: 0

ModelOriented/treeshap

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

Language: R - Size: 19.7 MB - Last synced at: 5 days ago - Pushed at: 11 months ago - Stars: 88 - Forks: 24

AndMastro/EdgeSHAPer

EdgeSHAPer: Bond-Centric Shapley Value-Based Explanation Method for Graph Neural Networks

Language: Jupyter Notebook - Size: 2.13 GB - Last synced at: 16 days ago - Pushed at: 16 days ago - Stars: 26 - Forks: 1

rachtibat/zennit-crp

An eXplainable AI toolkit with Concept Relevance Propagation and Relevance Maximization

Language: Jupyter Notebook - Size: 17.9 MB - Last synced at: 17 days ago - Pushed at: 12 months ago - Stars: 127 - Forks: 18

jacobgil/vit-explain

Explainability for Vision Transformers

Language: Python - Size: 4.11 MB - Last synced at: 14 days ago - Pushed at: about 3 years ago - Stars: 958 - Forks: 103

maxreiss123/GeneExpressionProgramming.jl

Gene Expression Programming for symbolic regression in Julia

Language: Julia - Size: 3.63 MB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 1 - Forks: 0

ScalaConsultants/Aspect-Based-Sentiment-Analysis

💭 Aspect-Based-Sentiment-Analysis: Transformer & Explainable ML (TensorFlow)

Language: Python - Size: 1.8 MB - Last synced at: 10 days ago - Pushed at: about 1 month ago - Stars: 570 - Forks: 90

deel-ai/xplique

👋 Xplique is a Neural Networks Explainability Toolbox

Language: Python - Size: 33.4 MB - Last synced at: 10 days ago - Pushed at: 8 months ago - Stars: 689 - Forks: 58

trustyai-explainability/trustyai-service-operator

TrustyAI's Kubernetes operator

Language: Go - Size: 1.25 MB - Last synced at: 17 days ago - Pushed at: 17 days ago - Stars: 5 - Forks: 33

fzi-forschungszentrum-informatik/TSInterpret

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

Language: Python - Size: 200 MB - Last synced at: 6 days ago - Pushed at: 6 months ago - Stars: 134 - Forks: 15

adaamko/POTATO

XAI based human-in-the-loop framework for automatic rule-learning.

Language: Jupyter Notebook - Size: 6.07 MB - Last synced at: 4 days ago - Pushed at: 11 months ago - Stars: 49 - Forks: 8

kevinqnb/interpretable-clustering

Methods and algorithms for interpretable clustering. Example applications to climate data.

Language: Python - Size: 208 MB - Last synced at: 3 days ago - Pushed at: 18 days ago - Stars: 0 - Forks: 0

AthenaCore/AwesomeResponsibleAI

A curated list of awesome academic research, books, code of ethics, data sets, institutes, maturity models, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible, Trustworthy, and Human-Centered AI.

Size: 1.21 MB - Last synced at: 18 days ago - Pushed at: 18 days ago - Stars: 72 - Forks: 14

EthicalML/xai

XAI - An eXplainability toolbox for machine learning

Language: Python - Size: 17.8 MB - Last synced at: 16 days ago - Pushed at: over 3 years ago - Stars: 1,171 - Forks: 179

HumbertoSGoncalves/SeeThroughPackets

Enhanced PacketWorx with Explainable AI (SHAP & LIME) for interpretable intrusion detection. Uses CIC-IDS2017-based ML models to classify and explain packet-level threats. Built for cybersecurity analysts and product managers seeking transparency in detection logic.

Language: Python - Size: 1.11 MB - Last synced at: 19 days ago - Pushed at: 19 days ago - Stars: 0 - Forks: 0