Explainability Interpretability Frameworks

Tools and frameworks for explaining, interpreting, and evaluating machine learning model predictions and decisions. Includes XAI methods, explanation techniques, robustness evaluation, and interpretability benchmarks. Does NOT include general model evaluation, performance metrics, or domain-specific applications (e.g., medical diagnosis, autonomous vehicles) unless focused on their interpretability aspects.

There are 223 explainability interpretability frameworks tracked. 6 score above 70 (verified tier). The highest-rated is obss/sahi at 81/100 with 5,160 stars. 5 of the top 10 are actively maintained.

Get all 223 projects as JSON

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#	Framework	Score	Tier	Stars	Language
1	obss/sahi Framework agnostic sliced/tiled inference + interactive ui + error analysis plots	81	Verified	5,160	Python
2	MAIF/shapash 🔅 Shapash: User-friendly Explainability and Interpretability to Develop...	79	Verified	3,150	Jupyter Notebook
3	SeldonIO/alibi Algorithms for explaining machine learning models	72	Verified	2,617	Python
4	understandable-machine-intelligence-lab/Quantus Quantus is an eXplainable AI toolkit for responsible evaluation of neural...	72	Verified	647	Jupyter Notebook
5	interpretml/interpret Fit interpretable models. Explain blackbox machine learning.	72	Verified	6,813	C++
6	ModelOriented/DALEX moDel Agnostic Language for Exploration and eXplanation	70	Verified	1,458	Python
7	jphall663/awesome-machine-learning-interpretability A curated list of awesome responsible machine learning resources.	69	Established	3,996	—
8	csinva/imodels Interpretable ML package 🔍 for concise, transparent, and accurate predictive...	68	Established	1,574	Jupyter Notebook
9	aixplain/aiXplain aiXplain enables python programmers to add AI functions to their software.	68	Established	50	Python
10	tensorflow/tcav Code for the TCAV ML interpretability project	67	Established	653	Jupyter Notebook
11	EthicalML/xai XAI - An eXplainability toolbox for machine learning	64	Established	1,229	Python
12	rachtibat/zennit-crp An eXplainable AI toolkit with Concept Relevance Propagation and Relevance...	63	Established	141	Jupyter Notebook
13	interpretml/interpret-community Interpret Community extends Interpret repository with additional...	62	Established	442	Python
14	Trusted-AI/AIX360 Interpretability and explainability of data and machine learning models	60	Established	1,767	Python
15	PAIR-code/what-if-tool Source code/webpage/demos for the What-If Tool	59	Established	992	HTML
16	PAIR-code/lit The Learning Interpretability Tool: Interactively analyze ML models to...	59	Established	3,640	TypeScript
17	TeamHG-Memex/eli5 A library for debugging/inspecting machine learning classifiers and...	57	Established	2,773	Jupyter Notebook
18	sergioburdisso/pyss3 A Python library for Interpretable Machine Learning in Text Classification...	57	Established	349	Python
19	sicara/tf-explain Interpretability Methods for tf.keras models with Tensorflow 2.x	56	Established	1,036	Python
20	PAIR-code/saliency Framework-agnostic implementation for state-of-the-art saliency methods...	54	Established	993	Jupyter Notebook
21	explainX/explainx Explainable AI framework for data scientists. Explain & debug any blackbox...	51	Established	445	Jupyter Notebook
22	Dependable-Intelligent-Systems-Lab/xwhy Explaining black boxes with a SMILE: Statistical Mode-agnostic...	50	Established	12	Jupyter Notebook
23	suinleelab/path_explain A repository for explaining feature attributions and feature interactions in...	50	Established	193	Jupyter Notebook
24	ombhojane/explainableai Increase interpretability of your models!	50	Established	28	Jupyter Notebook
25	artefactory/woodtapper WoodTapper — a Python toolbox for interpretable and explainable tree ensembles.	50	Established	36	Python
26	AustinRochford/PyCEbox ⬛ Python Individual Conditional Expectation Plot Toolbox	49	Emerging	163	Jupyter Notebook
27	salesforce/OmniXAI OmniXAI: A Library for eXplainable AI	48	Emerging	963	Jupyter Notebook
28	tensorflow/lucid A collection of infrastructure and tools for research in neural network...	48	Emerging	4,703	Jupyter Notebook
29	mateoespinosa/cem Repository for our NeurIPS 2022 paper "Concept Embedding Models", our...	48	Emerging	73	Python
30	awsm-research/PyExplainer PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)	47	Emerging	30	Python
31	TrusteeML/trustee This package implements the trustee framework to extract decision tree...	45	Emerging	33	Python
32	BCG-X-Official/facet Human-explainable AI.	45	Emerging	531	Jupyter Notebook
33	Telefonica/XAIoGraphs XAIoGraphs (eXplainability Articicial Intelligence over Graphs) is an...	45	Emerging	3	Python
34	linkedin/TE2Rules Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.	44	Emerging	63	Python
35	interpretml/DiCE Generate Diverse Counterfactual Explanations for any machine learning model.	43	Emerging	1,499	Python
36	sbobek/tsproto Post-hoc prototype-based explanations with rules for time-series classifiers	43	Emerging	6	Python
37	josephenguehard/time_interpret Unified Model Interpretability Library for Time Series	43	Emerging	72	Python
38	flyingdoog/awesome-graph-explainability-papers Papers about explainability of GNNs	42	Emerging	794	—
39	suinleelab/attributionpriors Tools for training explainable models using attribution priors.	42	Emerging	125	Jupyter Notebook
40	edahelsinki/slisemap SLISEMAP: Combining supervised dimensionality reduction with local explanations	42	Emerging	21	Python
41	carla-recourse/CARLA CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual...	42	Emerging	300	Python
42	breimanntools/aaanalysis Python framework for interpretable protein prediction	42	Emerging	82	Jupyter Notebook
43	oneTaken/awesome_deep_learning_interpretability 深度学习近年来关于神经网络模型解释性的相关高引用/顶会论文(附带代码)	42	Emerging	764	—
44	carpentries-incubator/fair-explainable-ml Fair and explainable ML workshop	41	Emerging	4	Jupyter Notebook
45	imatge-upc/SurvLIMEpy Local interpretability for survival models	41	Emerging	24	Python
46	tdlabs-ai/tanml Automated validation toolkit for tabular ML models in finance and regulated domains.	40	Emerging	7	Python
47	gregversteeg/CorEx CorEx or "Correlation Explanation" discovers a hierarchy of informative...	40	Emerging	307	Python
48	ottenbreit-data-science/aplr APLR builds predictive, interpretable regression and classification models...	40	Emerging	23	C++
49	Lexsi-Labs/DLBacktrace DL Backtrace is a new explainablity technique for deep learning models that...	40	Emerging	24	Python
50	charmlab/recourse_benchmarks A package for Displaying and Computing Benchmarking Results of Algorithmic...	39	Emerging	8	Python
51	alexzwanenburg/familiar Repository for the familiar R-package. Familiar implements an end-to-end...	38	Emerging	31	R
52	Montimage/maip A platform that provides users with easy access to AI services developed by...	38	Emerging	10	JavaScript
53	jacobgil/vit-explain Explainability for Vision Transformers	38	Emerging	1,072	Python
54	google-research/reverse-engineering-neural-networks A collection of tools for reverse engineering neural networks.	38	Emerging	168	Jupyter Notebook
55	idealo/cnn-exposed 🕵️‍♂️ Interpreting Convolutional Neural Network (CNN) Results.	38	Emerging	176	Jupyter Notebook
56	dylan-slack/Fooling-LIME-SHAP Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)	37	Emerging	84	Jupyter Notebook
57	JuliaTrustworthyAI/CounterfactualExplanations.jl A package for Counterfactual Explanations and Algorithmic Recourse in Julia.	37	Emerging	127	Julia
58	AstraZeneca/awesome-explainable-graph-reasoning A collection of research papers and software related to explainability in...	37	Emerging	1,985	—
59	csinva/hierarchical-dnn-interpretations Using / reproducing ACD from the paper "Hierarchical interpretations for...	37	Emerging	129	Jupyter Notebook
60	adc-trust-ai/trust-free An interpretable regression model in Python with Random-Forest-level accuracy	36	Emerging	11	Jupyter Notebook
61	LambdaSection/NeuralDBG A causal inference engine for deep learning training that provides...	36	Emerging	20	Python
62	SquareResearchCenter-AI/BEExAI Benchmark to Evaluate EXplainable AI	36	Emerging	20	Python
63	xplainable/xplainable Real-time explainable machine learning for business optimisation	36	Emerging	64	Python
64	Yu-Group/imodels-experiments Experiments with experimental rule-based models to go along with imodels.	36	Emerging	18	Jupyter Notebook
65	jphall663/interpretable_machine_learning_with_python Examples of techniques for training interpretable ML models, explaining ML...	36	Emerging	680	Jupyter Notebook
66	h2oai/mli-resources H2O.ai Machine Learning Interpretability Resources	36	Emerging	491	Jupyter Notebook
67	poloclub/webshap JavaScript library to explain any machine learning models anywhere!	36	Emerging	68	TypeScript
68	inouye-lab/ShapleyExplanationNetworks Implementation of the paper "Shapley Explanation Networks"	35	Emerging	88	Python
69	Crisp-Unimib/ContrXT a tool for comparing the predictions of any text classifiers	35	Emerging	27	Python
70	solegalli/machine-learning-interpretability Code repository for the online course Machine Learning Interpretability	35	Emerging	30	Jupyter Notebook
71	viadee/javaAnchorExplainer Explains machine learning models fast using the Anchor algorithm originally...	35	Emerging	15	Java
72	mmschlk/iXAI Fast and incremental explanations for online machine learning models. Works...	35	Emerging	55	Python
73	microsoft/responsible-ai-workshop Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate...	35	Emerging	47	Jupyter Notebook
74	serre-lab/Harmonization 👋 Aligning Human & Machine Vision using explainability	35	Emerging	53	Python
75	dylan-slack/Modeling-Uncertainty-Local-Explainability Local explanations with uncertainty 💐!	35	Emerging	42	Python
76	VincentGranville/Machine-Learning Material related to my book Intuitive Machine Learning. Some of this...	34	Emerging	125	Python
77	Yu-Group/adaptive-wavelets Adaptive, interpretable wavelets across domains (NeurIPS 2021)	34	Emerging	83	Jupyter Notebook
78	fredhohman/summit 🏔️ Summit: Scaling Deep Learning Interpretability by Visualizing Activation...	34	Emerging	116	JavaScript
79	pietrobarbiero/pytorch_explain PyTorch Explain: Interpretable Deep Learning in Python.	33	Emerging	172	Jupyter Notebook
80	JonathanCrabbe/Label-Free-XAI This repository contains the implementation of Label-Free XAI, a new...	33	Emerging	25	Python
81	alstonlo/torch-influence A simple PyTorch implementation of influence functions.	33	Emerging	92	Python
82	giacoballoccu/explanation-quality-recsys Post Processing Explanations Paths in Path Reasoning Recommender Systems...	33	Emerging	35	Python
83	aimclub/StableGNN Framework for autonomous learning of explainable graph neural networks	32	Emerging	33	Jupyter Notebook
84	valevalerio/saliencytools Saliency Metrics is a Python package that implements various metrics for...	32	Emerging	3	Jupyter Notebook
85	krisrs1128/stat479_notes Course notes for Undergraduate Interpretable Machine Learning at UW-Madison.	32	Emerging	6	HTML
86	Yu-Group/clinical-rule-vetting Learning clinical-decision rules with interpretable models.	32	Emerging	21	Jupyter Notebook
87	ServiceNow/azimuth Helping AI practitioners better understand their datasets and models in text...	32	Emerging	72	Python
88	JonathanCrabbe/Simplex This repository contains the implementation of SimplEx, a method to explain...	32	Emerging	24	Python
89	lowe-lab-ucl/cellx-predict Explainable AI model of cell behavior	32	Emerging	20	Python
90	alethia-xai/obzai Obz AI 🔍: Explainable AI, Model Monitoring, and Outlier Detection for Computer Vision	32	Emerging	5	Jupyter Notebook
91	pbiecek/ema Explanatory Model Analysis. Explore, Explain and Examine Predictive Models	32	Emerging	198	Jupyter Notebook
92	laura-rieger/deep-explanation-penalization Code for using CDEP from the paper "Interpretations are useful: penalizing...	32	Emerging	128	Jupyter Notebook
93	dilyabareeva/quanda A toolkit for quantitative evaluation of data attribution methods.	31	Emerging	57	Jupyter Notebook
94	alevas/xai_similarity_transformers Implementation for the paper Explaining Text Similarity in Transformer Models	31	Emerging	5	Jupyter Notebook
95	Trustworthy-ML-Lab/Label-free-CBM [ICLR 23] A new framework to transform any neural networks into an...	31	Emerging	133	Jupyter Notebook
96	i6092467/semi-supervised-multiview-cbm Concept bottleneck models for multiview data with incomplete concept sets	31	Emerging	16	Python
97	cambridge-mlg/CLUE Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"	31	Emerging	35	Python
98	rikhuijzer/SIRUS.jl Interpretable Machine Learning via Rule Extraction	30	Emerging	40	Julia
99	fengtong-xiao/DMBGN The implementation of the accepted paper "Deep Multi-Behaviors Graph Network...	30	Emerging	14	Jupyter Notebook
100	trustyai-explainability/trustyai-explainability-python-examples Examples for the Python bindings for TrustyAI's explainability library	30	Emerging	13	—
101	salimamoukou/acv00 ACV is a python library that provides explanations for any machine learning...	30	Emerging	102	Jupyter Notebook
102	intel/intel-xai-tools Explainable AI Tooling (XAI). XAI is used to discover and explain a model's...	30	Emerging	39	Jupyter Notebook
103	interpretml/gam-changer Editing machine learning models to reflect human knowledge and values	30	Emerging	128	JavaScript
104	hi-paris/XPER A methodology designed to measure the contribution of the features to the...	29	Experimental	18	Python
105	Karim-53/Compare-xAI A Unified Approach to Evaluate and Compare Explainable AI methods	29	Experimental	14	Jupyter Notebook
106	yolandalalala/GNNBoundary [ICLR 2024] Official implementation of the paper "GNNBoundary"	29	Experimental	5	Jupyter Notebook
107	mdhabibi/LIME-for-Time-Series LIME for TimeSeries enhances AI transparency by providing LIME-based...	29	Experimental	15	Jupyter Notebook
108	jim-berend/semanticlens Mechanistic understanding and validation of large AI models with SemanticLens	28	Experimental	51	Python
109	evandez/neuron-descriptions Natural Language Descriptions of Deep Visual Features, ICLR 2022	28	Experimental	65	Python
110	csinva/disentangled-attribution-curves Using / reproducing DAC from the paper "Disentangled Attribution Curves for...	28	Experimental	28	Python
111	epfl-ml4ed/evaluating-explainers Comparing 5 different XAI techniques (LIME, PermSHAP, KernelSHAP, DiCE, CEM)...	28	Experimental	17	PureBasic
112	mim-uw/eXplainableMachineLearning-2023 eXplainable Machine Learning 2022 at MIM UW	28	Experimental	20	Jupyter Notebook
113	sibyl-dev/VBridge Visualization for Explainable Healthcare Models	28	Experimental	16	TypeScript
114	chus-chus/teex A Toolbox for the Evaluation of machine learning Explanations	28	Experimental	16	Python
115	dailab/MAXi-XAI-lib A model-agnostic library for generating explanations of machine learning...	27	Experimental	9	Jupyter Notebook
116	sukrutrao/Model-Guidance Code for the paper: Studying How to Efficiently and Effectively Guide Models...	27	Experimental	19	Python
117	bmi-labmedinfo/araucana-xai Tree-based local explanations of machine learning model predictions	27	Experimental	6	Jupyter Notebook
118	braindatalab/xai-tris XAI-Tris	27	Experimental	3	Jupyter Notebook
119	Trustworthy-ML-Lab/CLIP-dissect [ICLR 23 spotlight] An automatic and efficient tool to describe...	27	Experimental	63	Jupyter Notebook
120	nyuvis/explanation_explorer A user interface to interpret machine learning models.	26	Experimental	71	JavaScript
121	poloclub/telegam TeleGam: Combining Visualization and Verbalization for Interpretable Machine Learning	26	Experimental	8	JavaScript
122	yolandalalala/GNNInterpreter [ICLR 2023] Official implementation of the paper "GNNInterpreter"	26	Experimental	16	Jupyter Notebook
123	lucacoma/XAISrcLoc Code repository for the paper Interpreting End-to-End Deep Learning Models...	26	Experimental	5	Jupyter Notebook
124	epfl-ml4ed/ripple Interpretability on raw time series with graph neural nets and concept...	26	Experimental	8	Jupyter Notebook
125	Selasie5/explainable-backend A Fast API Backend Engine for explainable- Turn raw datasets and machine...	26	Experimental	3	Python
126	ukuhl/IntroAlienZoo Introducing the Alien Zoo approach: An experimental framework for evaluating...	26	Experimental	4	JavaScript
127	faatehim/xplain :earth_americas: Complex Topics Explained For Your Level And Background. :pencil2:	25	Experimental	42	HTML
128	lucasdavid/keras-explainable Efficient explaining AI algorithms for Keras models	25	Experimental	15	Python
129	lkopf/cosy [NeurIPS 2024] CoSy is an automatic evaluation framework for textual...	25	Experimental	19	Jupyter Notebook
130	visual-ds/plausible-nlp-explanations Code and data of the paper "Exploring the Trade-off Between Model...	25	Experimental	5	Jupyter Notebook
131	mateoespinosa/tabcbm Official Implementation of TMLR's paper: "TabCBM: Concept-based...	25	Experimental	15	Python
132	baldassarreFe/graph-network-explainability Explainability techniques for Graph Networks, applied to a synthetic dataset...	25	Experimental	127	Jupyter Notebook
133	bgreenwell/ebm Explainable Boosting Machines	25	Experimental	5	R
134	AFAgarap/dnn-trust How can I trust you? An intuition and tutorial on trust score	25	Experimental	4	Jupyter Notebook
135	sungyubkim/gex Official code implementation of "GEX: A flexible method for approximating...	24	Experimental	14	Python
136	csbg/pnet_robustness Reliable interpretability of biology-inspired deep neural networks	24	Experimental	3	R
137	soumyadip1995/TCAV ⚙📲Interpretability Beyond Feature Attribution: Quantitative Testing with...	24	Experimental	3	Jupyter Notebook
138	GlassAlpha/glassalpha GlassAlpha is an open-source toolkit for deterministic, regulator-ready ML...	24	Experimental	2	Python
139	ypeiyu/attribution_recalibration [ICLR 2023 Spotlight] Re-calibrating Feature Attributions for Model Interpretation	24	Experimental	47	Python
140	ajsanjoaquin/mPerturb Implementation of Interpretable Explanations of Black Boxes by Meaningful...	23	Experimental	6	Jupyter Notebook
141	MarcoParola/CIProVA-framework Human-centered XAI via a Concept-Informed Prompt-based Validation framework...	23	Experimental	8	Python
142	VectorInstitute/interpretability Interpretability bootcamp reference implementations	23	Experimental	6	Jupyter Notebook
143	viadee/magie Interpret all the models - a genetic optimization approach to model agnostic...	23	Experimental	6	Java
144	adc-trust-ai/whitebox-ai-syllabus A curated syllabus for mastering Interpretable ML: From math foundations to...	23	Experimental	1	—
145	vanderschaarlab/clairvoyance2 clairvoyance2: a Unified Toolkit for Medical Time Series	23	Experimental	2	Python
146	SasageyoOrg/explainable-ai Approaching to XAI interpreting Deep Neural Networks through a Decision Tree...	23	Experimental	2	Prolog
147	LukasKarner/IT4PXAI This is the repository of my master's thesis "Information theory for...	23	Experimental	1	Jupyter Notebook
148	pyartemis/artemis A Python package with explanation methods for extraction of feature...	22	Experimental	33	Jupyter Notebook
149	Gehoren/interpretable-neural-basis-decomposition 🔍 Explore how Multi-Layer Perceptrons work by visualizing function...	22	Experimental	—	Python
150	aravikishan/MLExplain Interactive ML model explainer with scikit-learn, feature importance, and...	22	Experimental	—	Python
151	asibic/glassalpha 🔍 Simplify ML compliance with GlassAlpha, an open-source toolkit for...	22	Experimental	—	Python
152	Eation5/Explainable-AI-Toolkit A toolkit for interpreting and explaining machine learning models, providing...	22	Experimental	—	Python
153	tirtharajdash/CRM Compositional Relational Machines (CRMs): Constructing deep neural networks...	22	Experimental	1	Perl
154	sebastian-lapuschkin/explaining-deep-clinical-gait-classification Code and Data used for the paper "Explaining Machine Learning Models for...	22	Experimental	37	Python
155	bejay678/qwen-whitebox-experiment White-boxing memory modules of Qwen2.5-0.5B-Instruct: 80x retrieval...	22	Experimental	—	Python
156	rogue-agent1/cronexplain Explain cron expressions in plain English. Zero deps.	22	Experimental	—	Python
157	arturoornelasb/reptimeline Track how discrete representations evolve during neural network training —...	22	Experimental	—	Python
158	TheBuleGanteng/interpretability-prototyping This project is an educational exploration of Large Language Model (LLM)...	22	Experimental	—	Jupyter Notebook
159	djib2011/hide-and-seek Repo for the paper: "Hide-and-Seek: A Template for Explainable AI", by...	22	Experimental	7	Jupyter Notebook
160	csinva/transformation-importance Using / reproducing TRIM from the paper "Transformation Importance with...	22	Experimental	9	Jupyter Notebook
161	cmu-sei/feud AI Division, Reverse Engineering CNN Trojans	22	Experimental	9	Python
162	Human-Centric-Machine-Learning/counterfactual-explanations-mdp Code for "Counterfactual Explanations in Sequential Decision Making Under...	22	Experimental	16	Jupyter Notebook
163	fanconic/this-does-not-look-like-that Code for the experiments of the ICML 2021 Interpretability workshop paper...	22	Experimental	20	Jupyter Notebook
164	vdlad/Remarkable-Robustness-of-LLMs Codebase the paper "The Remarkable Robustness of LLMs: Stages of Inference?"	22	Experimental	19	Jupyter Notebook
165	PERSIMUNE/explainer ExplaineR is an R package built for enhanced interpretation of...	21	Experimental	21	R
166	MarcelRobeer/explabox Explore/examine/explain/expose your model with the explabox!	21	Experimental	19	Python
167	zichuan-liu/TimeXplusplus [ICML'24] Official PyTorch Implementation of TimeX++	21	Experimental	30	Python
168	sMamooler/CLIP_Explainability code for studying OpenAI's CLIP explainability	20	Experimental	38	Jupyter Notebook
169	serval-uni-lu/confetti Counterfactual explanations for multivariate time series classifiers.	20	Experimental	11	Python
170	matt-seb-ho/WikiWhy WikiWhy is a new benchmark for evaluating LLMs' ability to explain between...	20	Experimental	48	Python
171	Michaelrobins938/first-principles-attribution First-principles attribution framework combining Markov chains (causality),...	19	Experimental	—	TypeScript
172	AslanDing/Robust-Fidelity a robust metric (robust fidelity) for XGNN (ICLR24)	19	Experimental	12	Python
173	JonathanCrabbe/RobustXAI This repository contains the implementation of the explanation invariance...	19	Experimental	10	Jupyter Notebook
174	adaruna3/explainable-kge Code repo of EXplainable Knowledge Graph Embedding paper (XKGE)	19	Experimental	9	Shell
175	CristianoPatricio/coherent-cbe-skin Code for the paper "Coherent Concept-based Explanations in Medical Image and...	19	Experimental	19	Python
176	xianglinyang/TimeVis Official source code for IJCAI 2022 Paper: Temporality Spatialization: A...	19	Experimental	9	Jupyter Notebook
177	arthur-batel/IMPACT Repository contaning the original code of IMPACT algorithm, an interpretable...	19	Experimental	6	Jupyter Notebook
178	lapalap/invert Official GitHub for the paper "Labeling Neural Representations with Inverse...	19	Experimental	10	Jupyter Notebook
179	viadee/xai_examples Things that call for explanations...	18	Experimental	4	Java
180	ypeiyu/LPI [AAAI 2023] Local path integration for attribution	18	Experimental	5	Python
181	SasankYadati/interpretability-in-neural-networks Compare traditional neural networks with self explaining neural networks in...	18	Experimental	5	Jupyter Notebook
182	iheb-brini/SegClarity SegClarity: An attribution-based XAI workflow for layer-wise...	18	Experimental	4	Jupyter Notebook
183	h-fuzzy-logic/explainability-fairness-safety-for-ai Resources to improve the explainability, fairness, and safety of your AI	18	Experimental	3	—
184	realMoana/ProxyExplainer ProxyExplainer for Graph Neural Networks	17	Experimental	15	Python
185	sandareka/Interpretability-of-Machine-Learning-Visualizations Interpretability of Machine Learning-Visualizations	17	Experimental	13	Python
186	karannb/interact Official Implementation for the intelligibility protocol (PXP).	17	Experimental	2	Python
187	GhadaElkhawaga/PPM_XAI_Comparison Code of experiments implemented in the paper "Explainability of Predictive...	17	Experimental	5	HTML
188	kevinmcareavey/chai-xai A collection of material on explainable AI (XAI) compiled for the CHAI project	16	Experimental	4	—
189	CristianoPatricio/concept-based-interpretability-VLM Code for the paper "Towards Concept-based Interpretability of Skin Lesion...	16	Experimental	14	Jupyter Notebook
190	JG91/CNNPRE CNNPRE: A CNN-Based Protocol Reverse Engineering Method	16	Experimental	10	Jupyter Notebook
191	burnpiro/xai-correlation XAI evaluation with popular methods	16	Experimental	3	Jupyter Notebook
192	Purushothaman-natarajan/VALE-Explainer Language-Aware Visual Explanations (LAVE) is a framework designed for image...	15	Experimental	2	Jupyter Notebook
193	cloudexplain/xaiflow Create beautiful, interactive charts for explainable AI using MLFlow	15	Experimental	7	JavaScript
194	daikikatsuragawa/awesome-counterfactual-explanations This repository is a curated collection of information (keywords, papers,...	15	Experimental	23	—
195	AntonotnaWang/HINT [CVPR 2022] HINT: Hierarchical Neuron Concept Explainer	15	Experimental	20	Jupyter Notebook
196	HSBC-RISE18/Explainable-AI This repository is being maintained by https://github.com/MohammadYousufHussain	15	Experimental	1	Jupyter Notebook
197	lazyCodes7/blacbox Making CNNs interpretable, because accuracy can't cut it anymore:p	14	Experimental	11	Jupyter Notebook
198	PERSIMUNE/MAIT Medical artificial intelligence toolbox (MAIT): an explainable machine...	14	Experimental	4	HTML
199	Scontel/ml-model-explainability Tools and techniques for interpreting and explaining machine learning model...	14	Experimental	—	Python
200	bmezaris/TAME Code and data for our learning-based eXplainable AI (XAI) method TAME: M....	14	Experimental	7	Python
201	nitin2468git/ml-explainability-toolkit ML model interpretability with SHAP, LIME, and Partial Dependence Plots	14	Experimental	—	Jupyter Notebook
202	mayankjoshiii/ml-explainability-dashboard ML Model Explainability & Monitoring Platform with SHAP-style explanations,...	14	Experimental	—	HTML
203	nikivanstein/GSAreport Global Sensitivity reporting for Explainable AI	14	Experimental	14	Python
204	apartresearch/deepdecipher 🦠 DeepDecipher: An open source API to MLP neurons	14	Experimental	9	Rust
205	hslyu/GIF Official implementation of "Deeper Understanding of Black-box Predictions...	14	Experimental	9	Jupyter Notebook
206	LamineTourelab/Explainable-AI In this repository you will fine explainability of machine learning models.	14	Experimental	9	—
207	rinnguyen0905/aiml-model-validation AI/ML Model Validation & Auditing Framework	14	Experimental	3	Jupyter Notebook
208	aycignl/peak PEAK: Explainable Privacy Assistant through Automated Knowledge Extraction	13	Experimental	2	Jupyter Notebook
209	medoidai/interpretable-machine-learning-blog-notebooks Notebook examples from "A Practical Overview of Interpretable Machine...	13	Experimental	6	Jupyter Notebook
210	Purushothaman-natarajan/eXplainable-AI-for-Image-Classification-on-Remote-Sensing This repository provides the training codes to classify aerial images using...	13	Experimental	5	Jupyter Notebook
211	viadee/javaAnchorAdapters Getting the Anchors Explainer to work in Different Settings	13	Experimental	5	Java
212	neelsomani/epistemic-stance-mechinterp Do models distinguish between declared-true and declared-false premises?	12	Experimental	11	Python
213	andresilvapimentel/RNAtox RNAtox is a code to classify the caspase toxicity and gene knockdown of...	12	Experimental	1	Jupyter Notebook
214	SMARTDXCLOUD/AI-MHE Meta-machine Learning and Explainable AI: Performance Prediction of Medical...	12	Experimental	—	Python
215	mitvis/saliency-cards Saliency Cards are transparency documentation for saliency methods. Learn...	12	Experimental	19	Jupyter Notebook
216	expai-io/expai-tutorials Repository containing sample datasets, models and notebooks to start using EXPAI.	11	Experimental	—	Jupyter Notebook
217	cslab-hub/LocalTSMHAInterpretability Visualization method of MHA which was trained on time series data, to...	11	Experimental	—	TypeScript
218	csinva/imodels-playground Demos for visualizing how rule-based models work.	11	Experimental	2	TypeScript
219	11301858/xaisuitecli CLI for XAISuite Library	11	Experimental	2	Go
220	DominiqueMercier/mislabel Code for the paper: Interpreting Deep Models through the Lens of Data	11	Experimental	—	Jupyter Notebook
221	cslab-hub/GlobalTimeSeriesCoherenceMatrices Code for the Paper Constructing Global Coherence Representations:Identifying...	10	Experimental	1	TypeScript
222	stchakwdev/NeuroMap Mechanistic interpretability framework for recovering algorithmic structure...	10	Experimental	3	Python
223	brendel-group/imi Official repository for the paper "Scale Alone Does not Improve Mechanistic...	10	Experimental	1	JavaScript

Comparisons in this category

interpret and awesome-machine-learning-interpretability (72 vs 69) shapash and interpret (79 vs 72) interpret and AIX360 (72 vs 60) interpret and imodels (72 vs 68) interpret and xai (72 vs 64) interpret and interpret-community (72 vs 62) shapash and awesome-machine-learning-interpretability (79 vs 69) shapash and AIX360 (79 vs 60) shapash and xai (79 vs 64) DALEX and AIX360 (70 vs 60)