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 234 explainability interpretability frameworks tracked. 3 score above 70 (verified tier). The highest-rated is obss/sahi at 75/100 with 5,160 stars. 5 of the top 10 are actively maintained.

Get all 234 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	75	Verified	5,160	Python
2	tensorflow/tcav Code for the TCAV ML interpretability project	70	Verified	653	Jupyter Notebook
3	MAIF/shapash 🔅 Shapash: User-friendly Explainability and Interpretability to Develop...	70	Verified	3,150	Jupyter Notebook
4	TeamHG-Memex/eli5 A library for debugging/inspecting machine learning classifiers and...	69	Established	2,773	Jupyter Notebook
5	csinva/imodels Interpretable ML package 🔍 for concise, transparent, and accurate predictive...	68	Established	1,574	Jupyter Notebook
6	interpretml/interpret Fit interpretable models. Explain blackbox machine learning.	67	Established	6,813	C++
7	ModelOriented/DALEX moDel Agnostic Language for Exploration and eXplanation	67	Established	1,458	Python
8	understandable-machine-intelligence-lab/Quantus Quantus is an eXplainable AI toolkit for responsible evaluation of neural...	66	Established	647	Jupyter Notebook
9	rachtibat/zennit-crp An eXplainable AI toolkit with Concept Relevance Propagation and Relevance...	65	Established	141	Jupyter Notebook
10	EthicalML/xai XAI - An eXplainability toolbox for machine learning	64	Established	1,229	Python
11	aixplain/aiXplain aiXplain enables python programmers to add AI functions to their software.	63	Established	50	Python
12	SeldonIO/alibi Algorithms for explaining machine learning models	62	Established	2,617	Python
13	jphall663/awesome-machine-learning-interpretability A curated list of awesome responsible machine learning resources.	62	Established	3,996	—
14	PAIR-code/saliency Framework-agnostic implementation for state-of-the-art saliency methods...	61	Established	993	Jupyter Notebook
15	PAIR-code/what-if-tool Source code/webpage/demos for the What-If Tool	60	Established	992	HTML
16	interpretml/interpret-community Interpret Community extends Interpret repository with additional...	59	Established	442	Python
17	Trusted-AI/AIX360 Interpretability and explainability of data and machine learning models	59	Established	1,767	Python
18	sergioburdisso/pyss3 A Python library for Interpretable Machine Learning in Text Classification...	58	Established	349	Python
19	AustinRochford/PyCEbox ⬛ Python Individual Conditional Expectation Plot Toolbox	56	Established	163	Jupyter Notebook
20	PAIR-code/lit The Learning Interpretability Tool: Interactively analyze ML models to...	56	Established	3,640	TypeScript
21	salesforce/OmniXAI OmniXAI: A Library for eXplainable AI	55	Established	963	Jupyter Notebook
22	sicara/tf-explain Interpretability Methods for tf.keras models with Tensorflow 2.x	55	Established	1,036	Python
23	mateoespinosa/cem Repository for our NeurIPS 2022 paper "Concept Embedding Models", our...	55	Established	73	Python
24	Dependable-Intelligent-Systems-Lab/xwhy Explaining black boxes with a SMILE: Statistical Mode-agnostic...	54	Established	12	Jupyter Notebook
25	explainX/explainx Explainable AI framework for data scientists. Explain & debug any blackbox...	53	Established	445	Jupyter Notebook
26	suinleelab/path_explain A repository for explaining feature attributions and feature interactions in...	53	Established	193	Jupyter Notebook
27	ombhojane/explainableai Increase interpretability of your models!	53	Established	28	Jupyter Notebook
28	BCG-X-Official/facet Human-explainable AI.	52	Established	531	Jupyter Notebook
29	interpretml/DiCE Generate Diverse Counterfactual Explanations for any machine learning model.	50	Established	1,499	Python
30	josephenguehard/time_interpret Unified Model Interpretability Library for Time Series	50	Established	72	Python
31	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)	49	Emerging	764	—
32	carla-recourse/CARLA CARLA: A Python Library to Benchmark Algorithmic Recourse and Counterfactual...	49	Emerging	300	Python
33	artefactory/woodtapper WoodTapper — a Python toolbox for interpretable and explainable tree ensembles.	49	Emerging	36	Python
34	awsm-research/PyExplainer PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)	49	Emerging	30	Python
35	tensorflow/lucid A collection of infrastructure and tools for research in neural network...	48	Emerging	4,703	Jupyter Notebook
36	TrusteeML/trustee This package implements the trustee framework to extract decision tree...	47	Emerging	33	Python
37	ottenbreit-data-science/aplr APLR builds predictive, interpretable regression and classification models...	47	Emerging	23	C++
38	gregversteeg/CorEx CorEx or "Correlation Explanation" discovers a hierarchy of informative...	47	Emerging	307	Python
39	Telefonica/XAIoGraphs XAIoGraphs (eXplainability Articicial Intelligence over Graphs) is an...	47	Emerging	3	Python
40	Lexsi-Labs/DLBacktrace DL Backtrace is a new explainablity technique for deep learning models that...	47	Emerging	24	Python
41	charmlab/recourse_benchmarks A package for Displaying and Computing Benchmarking Results of Algorithmic...	46	Emerging	8	Python
42	flyingdoog/awesome-graph-explainability-papers Papers about explainability of GNNs	46	Emerging	794	—
43	sbobek/tsproto Post-hoc prototype-based explanations with rules for time-series classifiers	46	Emerging	6	Python
44	Montimage/maip A platform that provides users with easy access to AI services developed by...	45	Emerging	10	JavaScript
45	breimanntools/aaanalysis Python framework for interpretable protein prediction	45	Emerging	82	Jupyter Notebook
46	jacobgil/vit-explain Explainability for Vision Transformers	45	Emerging	1,072	Python
47	carpentries-incubator/fair-explainable-ml Fair and explainable ML workshop	45	Emerging	4	Jupyter Notebook
48	google-research/reverse-engineering-neural-networks A collection of tools for reverse engineering neural networks.	45	Emerging	168	Jupyter Notebook
49	alexzwanenburg/familiar Repository for the familiar R-package. Familiar implements an end-to-end...	45	Emerging	31	R
50	linkedin/TE2Rules Python library to explain Tree Ensemble models (TE) like XGBoost, using a rule list.	45	Emerging	63	Python
51	idealo/cnn-exposed 🕵️‍♂️ Interpreting Convolutional Neural Network (CNN) Results.	45	Emerging	176	Jupyter Notebook
52	suinleelab/attributionpriors Tools for training explainable models using attribution priors.	45	Emerging	125	Jupyter Notebook
53	JuliaTrustworthyAI/CounterfactualExplanations.jl A package for Counterfactual Explanations and Algorithmic Recourse in Julia.	44	Emerging	127	Julia
54	csinva/hierarchical-dnn-interpretations Using / reproducing ACD from the paper "Hierarchical interpretations for...	44	Emerging	129	Jupyter Notebook
55	edahelsinki/slisemap SLISEMAP: Combining supervised dimensionality reduction with local explanations	44	Emerging	21	Python
56	imatge-upc/SurvLIMEpy Local interpretability for survival models	44	Emerging	24	Python
57	dylan-slack/Fooling-LIME-SHAP Adversarial Attacks on Post Hoc Explanation Techniques (LIME/SHAP)	44	Emerging	84	Jupyter Notebook
58	AstraZeneca/awesome-explainable-graph-reasoning A collection of research papers and software related to explainability in...	44	Emerging	1,985	—
59	jphall663/interpretable_machine_learning_with_python Examples of techniques for training interpretable ML models, explaining ML...	43	Emerging	680	Jupyter Notebook
60	h2oai/mli-resources H2O.ai Machine Learning Interpretability Resources	43	Emerging	491	Jupyter Notebook
61	tdlabs-ai/tanml Automated validation toolkit for tabular ML models in finance and regulated domains.	43	Emerging	7	Python
62	poloclub/webshap JavaScript library to explain any machine learning models anywhere!	43	Emerging	68	TypeScript
63	xplainable/xplainable Real-time explainable machine learning for business optimisation	43	Emerging	64	Python
64	microsoft/responsible-ai-workshop Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate...	42	Emerging	47	Jupyter Notebook
65	mmschlk/iXAI Fast and incremental explanations for online machine learning models. Works...	42	Emerging	55	Python
66	inouye-lab/ShapleyExplanationNetworks Implementation of the paper "Shapley Explanation Networks"	42	Emerging	88	Python
67	solegalli/machine-learning-interpretability Code repository for the online course Machine Learning Interpretability	42	Emerging	30	Jupyter Notebook
68	serre-lab/Harmonization 👋 Aligning Human & Machine Vision using explainability	42	Emerging	53	Python
69	dylan-slack/Modeling-Uncertainty-Local-Explainability Local explanations with uncertainty 💐!	42	Emerging	42	Python
70	viadee/javaAnchorExplainer Explains machine learning models fast using the Anchor algorithm originally...	42	Emerging	15	Java
71	fredhohman/summit 🏔️ Summit: Scaling Deep Learning Interpretability by Visualizing Activation...	41	Emerging	116	JavaScript
72	VincentGranville/Machine-Learning Material related to my book Intuitive Machine Learning. Some of this...	41	Emerging	125	Python
73	Yu-Group/adaptive-wavelets Adaptive, interpretable wavelets across domains (NeurIPS 2021)	41	Emerging	83	Jupyter Notebook
74	Yu-Group/imodels-experiments Experiments with experimental rule-based models to go along with imodels.	40	Emerging	18	Jupyter Notebook
75	alstonlo/torch-influence A simple PyTorch implementation of influence functions.	40	Emerging	92	Python
76	LambdaSection/NeuralDBG A causal inference engine for deep learning training that provides...	40	Emerging	20	Python
77	pietrobarbiero/pytorch_explain PyTorch Explain: Interpretable Deep Learning in Python.	40	Emerging	172	Jupyter Notebook
78	JonathanCrabbe/Label-Free-XAI This repository contains the implementation of Label-Free XAI, a new...	40	Emerging	25	Python
79	giacoballoccu/explanation-quality-recsys Post Processing Explanations Paths in Path Reasoning Recommender Systems...	40	Emerging	35	Python
80	SquareResearchCenter-AI/BEExAI Benchmark to Evaluate EXplainable AI	39	Emerging	20	Python
81	Yu-Group/clinical-rule-vetting Learning clinical-decision rules with interpretable models.	39	Emerging	21	Jupyter Notebook
82	pbiecek/ema Explanatory Model Analysis. Explore, Explain and Examine Predictive Models	39	Emerging	198	Jupyter Notebook
83	ServiceNow/azimuth Helping AI practitioners better understand their datasets and models in text...	39	Emerging	72	Python
84	adc-trust-ai/trust-free An interpretable regression model in Python with Random-Forest-level accuracy	39	Emerging	11	Jupyter Notebook
85	laura-rieger/deep-explanation-penalization Code for using CDEP from the paper "Interpretations are useful: penalizing...	39	Emerging	128	Jupyter Notebook
86	krisrs1128/stat479_notes Course notes for Undergraduate Interpretable Machine Learning at UW-Madison.	39	Emerging	6	HTML
87	Crisp-Unimib/ContrXT a tool for comparing the predictions of any text classifiers	39	Emerging	27	Python
88	aimclub/StableGNN Framework for autonomous learning of explainable graph neural networks	39	Emerging	33	Jupyter Notebook
89	lowe-lab-ucl/cellx-predict Explainable AI model of cell behavior	39	Emerging	20	Python
90	JonathanCrabbe/Simplex This repository contains the implementation of SimplEx, a method to explain...	39	Emerging	24	Python
91	i6092467/semi-supervised-multiview-cbm Concept bottleneck models for multiview data with incomplete concept sets	38	Emerging	16	Python
92	Trustworthy-ML-Lab/Label-free-CBM [ICLR 23] A new framework to transform any neural networks into an...	38	Emerging	133	Jupyter Notebook
93	cambridge-mlg/CLUE Code for the paper "Getting a CLUE: A Method for Explaining Uncertainty Estimates"	38	Emerging	35	Python
94	intel/intel-xai-tools Explainable AI Tooling (XAI). XAI is used to discover and explain a model's...	37	Emerging	39	Jupyter Notebook
95	rikhuijzer/SIRUS.jl Interpretable Machine Learning via Rule Extraction	37	Emerging	40	Julia
96	trustyai-explainability/trustyai-explainability-python-examples Examples for the Python bindings for TrustyAI's explainability library	37	Emerging	13	—
97	interpretml/gam-changer Editing machine learning models to reflect human knowledge and values	37	Emerging	128	JavaScript
98	salimamoukou/acv00 ACV is a python library that provides explanations for any machine learning...	37	Emerging	102	Jupyter Notebook
99	fengtong-xiao/DMBGN The implementation of the accepted paper "Deep Multi-Behaviors Graph Network...	37	Emerging	14	Jupyter Notebook
100	yolandalalala/GNNBoundary [ICLR 2024] Official implementation of the paper "GNNBoundary"	36	Emerging	5	Jupyter Notebook
101	hi-paris/XPER A methodology designed to measure the contribution of the features to the...	36	Emerging	18	Python
102	Karim-53/Compare-xAI A Unified Approach to Evaluate and Compare Explainable AI methods	36	Emerging	14	Jupyter Notebook
103	mdhabibi/LIME-for-Time-Series LIME for TimeSeries enhances AI transparency by providing LIME-based...	36	Emerging	15	Jupyter Notebook
104	dilyabareeva/quanda A toolkit for quantitative evaluation of data attribution methods.	35	Emerging	57	Jupyter Notebook
105	sibyl-dev/VBridge Visualization for Explainable Healthcare Models	35	Emerging	16	TypeScript
106	evandez/neuron-descriptions Natural Language Descriptions of Deep Visual Features, ICLR 2022	35	Emerging	65	Python
107	mim-uw/eXplainableMachineLearning-2023 eXplainable Machine Learning 2022 at MIM UW	35	Emerging	20	Jupyter Notebook
108	epfl-ml4ed/evaluating-explainers Comparing 5 different XAI techniques (LIME, PermSHAP, KernelSHAP, DiCE, CEM)...	35	Emerging	17	PureBasic
109	csinva/disentangled-attribution-curves Using / reproducing DAC from the paper "Disentangled Attribution Curves for...	35	Emerging	28	Python
110	jim-berend/semanticlens Mechanistic understanding and validation of large AI models with SemanticLens	35	Emerging	51	Python
111	alethia-xai/obzai Obz AI 🔍: Explainable AI, Model Monitoring, and Outlier Detection for Computer Vision	35	Emerging	5	Jupyter Notebook
112	sukrutrao/Model-Guidance Code for the paper: Studying How to Efficiently and Effectively Guide Models...	34	Emerging	19	Python
113	braindatalab/xai-tris XAI-Tris	34	Emerging	3	Jupyter Notebook
114	Trustworthy-ML-Lab/CLIP-dissect [ICLR 23 spotlight] An automatic and efficient tool to describe...	34	Emerging	63	Jupyter Notebook
115	bmi-labmedinfo/araucana-xai Tree-based local explanations of machine learning model predictions	34	Emerging	6	Jupyter Notebook
116	epfl-ml4ed/ripple Interpretability on raw time series with graph neural nets and concept...	33	Emerging	8	Jupyter Notebook
117	valevalerio/saliencytools Saliency Metrics is a Python package that implements various metrics for...	33	Emerging	3	Jupyter Notebook
118	lucacoma/XAISrcLoc Code repository for the paper Interpreting End-to-End Deep Learning Models...	33	Emerging	5	Jupyter Notebook
119	yolandalalala/GNNInterpreter [ICLR 2023] Official implementation of the paper "GNNInterpreter"	33	Emerging	16	Jupyter Notebook
120	Selasie5/explainable-backend A Fast API Backend Engine for explainable- Turn raw datasets and machine...	33	Emerging	3	Python
121	nyuvis/explanation_explorer A user interface to interpret machine learning models.	33	Emerging	71	JavaScript
122	ukuhl/IntroAlienZoo Introducing the Alien Zoo approach: An experimental framework for evaluating...	33	Emerging	4	JavaScript
123	poloclub/telegam TeleGam: Combining Visualization and Verbalization for Interpretable Machine Learning	33	Emerging	8	JavaScript
124	lucasdavid/keras-explainable Efficient explaining AI algorithms for Keras models	32	Emerging	15	Python
125	baldassarreFe/graph-network-explainability Explainability techniques for Graph Networks, applied to a synthetic dataset...	32	Emerging	127	Jupyter Notebook
126	AFAgarap/dnn-trust How can I trust you? An intuition and tutorial on trust score	32	Emerging	4	Jupyter Notebook
127	lkopf/cosy [NeurIPS 2024] CoSy is an automatic evaluation framework for textual...	32	Emerging	19	Jupyter Notebook
128	mateoespinosa/tabcbm Official Implementation of TMLR's paper: "TabCBM: Concept-based...	32	Emerging	15	Python
129	faatehim/xplain :earth_americas: Complex Topics Explained For Your Level And Background. :pencil2:	32	Emerging	42	HTML
130	bgreenwell/ebm Explainable Boosting Machines	32	Emerging	5	R
131	csbg/pnet_robustness Reliable interpretability of biology-inspired deep neural networks	31	Emerging	3	R
132	dailab/MAXi-XAI-lib A model-agnostic library for generating explanations of machine learning...	31	Emerging	9	Jupyter Notebook
133	chus-chus/teex A Toolbox for the Evaluation of machine learning Explanations	31	Emerging	16	Python
134	ypeiyu/attribution_recalibration [ICLR 2023 Spotlight] Re-calibrating Feature Attributions for Model Interpretation	31	Emerging	47	Python
135	sungyubkim/gex Official code implementation of "GEX: A flexible method for approximating...	31	Emerging	14	Python
136	soumyadip1995/TCAV ⚙📲Interpretability Beyond Feature Attribution: Quantitative Testing with...	31	Emerging	3	Jupyter Notebook
137	vanderschaarlab/clairvoyance2 clairvoyance2: a Unified Toolkit for Medical Time Series	30	Emerging	2	Python
138	MarcoParola/CIProVA-framework Human-centered XAI via a Concept-Informed Prompt-based Validation framework...	30	Emerging	8	Python
139	VectorInstitute/interpretability Interpretability bootcamp reference implementations	30	Emerging	6	Jupyter Notebook
140	SasageyoOrg/explainable-ai Approaching to XAI interpreting Deep Neural Networks through a Decision Tree...	30	Emerging	2	Prolog
141	LukasKarner/IT4PXAI This is the repository of my master's thesis "Information theory for...	30	Emerging	1	Jupyter Notebook
142	GlassAlpha/glassalpha GlassAlpha is an open-source toolkit for deterministic, regulator-ready ML...	30	Emerging	2	Python
143	ajsanjoaquin/mPerturb Implementation of Interpretable Explanations of Black Boxes by Meaningful...	30	Emerging	6	Jupyter Notebook
144	csinva/transformation-importance Using / reproducing TRIM from the paper "Transformation Importance with...	29	Experimental	9	Jupyter Notebook
145	vdlad/Remarkable-Robustness-of-LLMs Codebase the paper "The Remarkable Robustness of LLMs: Stages of Inference?"	29	Experimental	19	Jupyter Notebook
146	Human-Centric-Machine-Learning/counterfactual-explanations-mdp Code for "Counterfactual Explanations in Sequential Decision Making Under...	29	Experimental	16	Jupyter Notebook
147	sebastian-lapuschkin/explaining-deep-clinical-gait-classification Code and Data used for the paper "Explaining Machine Learning Models for...	29	Experimental	37	Python
148	pyartemis/artemis A Python package with explanation methods for extraction of feature...	29	Experimental	33	Jupyter Notebook
149	fanconic/this-does-not-look-like-that Code for the experiments of the ICML 2021 Interpretability workshop paper...	29	Experimental	20	Jupyter Notebook
150	cmu-sei/feud AI Division, Reverse Engineering CNN Trojans	29	Experimental	9	Python
151	djib2011/hide-and-seek Repo for the paper: "Hide-and-Seek: A Template for Explainable AI", by...	29	Experimental	7	Jupyter Notebook
152	tirtharajdash/CRM Compositional Relational Machines (CRMs): Constructing deep neural networks...	29	Experimental	1	Perl
153	zichuan-liu/TimeXplusplus [ICML'24] Official PyTorch Implementation of TimeX++	28	Experimental	30	Python
154	PERSIMUNE/explainer ExplaineR is an R package built for enhanced interpretation of...	28	Experimental	21	R
155	matt-seb-ho/WikiWhy WikiWhy is a new benchmark for evaluating LLMs' ability to explain between...	27	Experimental	48	Python
156	serval-uni-lu/confetti Counterfactual explanations for multivariate time series classifiers.	27	Experimental	11	Python
157	sMamooler/CLIP_Explainability code for studying OpenAI's CLIP explainability	27	Experimental	38	Jupyter Notebook
158	lapalap/invert Official GitHub for the paper "Labeling Neural Representations with Inverse...	26	Experimental	10	Jupyter Notebook
159	xianglinyang/TimeVis Official source code for IJCAI 2022 Paper: Temporality Spatialization: A...	26	Experimental	9	Jupyter Notebook
160	AslanDing/Robust-Fidelity a robust metric (robust fidelity) for XGNN (ICLR24)	26	Experimental	12	Python
161	JonathanCrabbe/RobustXAI This repository contains the implementation of the explanation invariance...	26	Experimental	10	Jupyter Notebook
162	adaruna3/explainable-kge Code repo of EXplainable Knowledge Graph Embedding paper (XKGE)	26	Experimental	9	Shell
163	CristianoPatricio/coherent-cbe-skin Code for the paper "Coherent Concept-based Explanations in Medical Image and...	26	Experimental	19	Python
164	arthur-batel/IMPACT Repository contaning the original code of IMPACT algorithm, an interpretable...	26	Experimental	6	Jupyter Notebook
165	ypeiyu/LPI [AAAI 2023] Local path integration for attribution	25	Experimental	5	Python
166	SasankYadati/interpretability-in-neural-networks Compare traditional neural networks with self explaining neural networks in...	25	Experimental	5	Jupyter Notebook
167	viadee/xai_examples Things that call for explanations...	25	Experimental	4	Java
168	h-fuzzy-logic/explainability-fairness-safety-for-ai Resources to improve the explainability, fairness, and safety of your AI	25	Experimental	3	—
169	MarcelRobeer/explabox Explore/examine/explain/expose your model with the explabox!	24	Experimental	19	Python
170	GhadaElkhawaga/PPM_XAI_Comparison Code of experiments implemented in the paper "Explainability of Predictive...	24	Experimental	5	HTML
171	iheb-brini/SegClarity SegClarity: An attribution-based XAI workflow for layer-wise...	24	Experimental	4	Jupyter Notebook
172	realMoana/ProxyExplainer ProxyExplainer for Graph Neural Networks	24	Experimental	15	Python
173	sandareka/Interpretability-of-Machine-Learning-Visualizations Interpretability of Machine Learning-Visualizations	24	Experimental	13	Python
174	burnpiro/xai-correlation XAI evaluation with popular methods	23	Experimental	3	Jupyter Notebook
175	adc-trust-ai/whitebox-ai-syllabus A curated syllabus for mastering Interpretable ML: From math foundations to...	23	Experimental	1	—
176	JG91/CNNPRE CNNPRE: A CNN-Based Protocol Reverse Engineering Method	23	Experimental	10	Jupyter Notebook
177	CristianoPatricio/concept-based-interpretability-VLM Code for the paper "Towards Concept-based Interpretability of Skin Lesion...	23	Experimental	14	Jupyter Notebook
178	kevinmcareavey/chai-xai A collection of material on explainable AI (XAI) compiled for the CHAI project	23	Experimental	4	—
179	daikikatsuragawa/awesome-counterfactual-explanations This repository is a curated collection of information (keywords, papers,...	22	Experimental	23	—
180	rogue-agent1/cronexplain Explain cron expressions in plain English. Zero deps.	22	Experimental	—	Python
181	Gehoren/interpretable-neural-basis-decomposition 🔍 Explore how Multi-Layer Perceptrons work by visualizing function...	22	Experimental	—	Python
182	aravikishan/MLExplain Interactive ML model explainer with scikit-learn, feature importance, and...	22	Experimental	—	Python
183	AntonotnaWang/HINT [CVPR 2022] HINT: Hierarchical Neuron Concept Explainer	22	Experimental	20	Jupyter Notebook
184	bejay678/qwen-whitebox-experiment White-boxing memory modules of Qwen2.5-0.5B-Instruct: 80x retrieval...	22	Experimental	—	Python
185	arturoornelasb/reptimeline Track how discrete representations evolve during neural network training —...	22	Experimental	—	Python
186	HSBC-RISE18/Explainable-AI This repository is being maintained by https://github.com/MohammadYousufHussain	22	Experimental	1	Jupyter Notebook
187	Purushothaman-natarajan/VALE-Explainer Language-Aware Visual Explanations (LAVE) is a framework designed for image...	22	Experimental	2	Jupyter Notebook
188	Eation5/Explainable-AI-Toolkit A toolkit for interpreting and explaining machine learning models, providing...	22	Experimental	—	Python
189	TheBuleGanteng/interpretability-prototyping This project is an educational exploration of Large Language Model (LLM)...	22	Experimental	—	Jupyter Notebook
190	asibic/glassalpha 🔍 Simplify ML compliance with GlassAlpha, an open-source toolkit for...	22	Experimental	—	Python
191	nikivanstein/GSAreport Global Sensitivity reporting for Explainable AI	21	Experimental	14	Python
192	Michaelrobins938/first-principles-attribution First-principles attribution framework combining Markov chains (causality),...	21	Experimental	—	TypeScript
193	lazyCodes7/blacbox Making CNNs interpretable, because accuracy can't cut it anymore:p	21	Experimental	11	Jupyter Notebook
194	apartresearch/deepdecipher 🦠 DeepDecipher: An open source API to MLP neurons	21	Experimental	9	Rust
195	cloudexplain/xaiflow Create beautiful, interactive charts for explainable AI using MLFlow	21	Experimental	7	JavaScript
196	bmezaris/TAME Code and data for our learning-based eXplainable AI (XAI) method TAME: M....	21	Experimental	7	Python
197	LamineTourelab/Explainable-AI In this repository you will fine explainability of machine learning models.	21	Experimental	9	—
198	PERSIMUNE/MAIT Medical artificial intelligence toolbox (MAIT): an explainable machine...	21	Experimental	4	HTML
199	hslyu/GIF Official implementation of "Deeper Understanding of Black-box Predictions...	21	Experimental	9	Jupyter Notebook
200	viadee/javaAnchorAdapters Getting the Anchors Explainer to work in Different Settings	20	Experimental	5	Java
201	rinnguyen0905/aiml-model-validation AI/ML Model Validation & Auditing Framework	20	Experimental	3	Jupyter Notebook
202	Purushothaman-natarajan/eXplainable-AI-for-Image-Classification-on-Remote-Sensing This repository provides the training codes to classify aerial images using...	20	Experimental	5	Jupyter Notebook
203	medoidai/interpretable-machine-learning-blog-notebooks Notebook examples from "A Practical Overview of Interpretable Machine...	20	Experimental	6	Jupyter Notebook
204	karannb/interact Official Implementation for the intelligibility protocol (PXP).	20	Experimental	2	Python
205	aycignl/peak PEAK: Explainable Privacy Assistant through Automated Knowledge Extraction	20	Experimental	2	Jupyter Notebook
206	mitvis/saliency-cards Saliency Cards are transparency documentation for saliency methods. Learn...	19	Experimental	19	Jupyter Notebook
207	csinva/imodels-playground Demos for visualizing how rule-based models work.	18	Experimental	2	TypeScript
208	cslab-hub/GlobalTimeSeriesCoherenceMatrices Code for the Paper Constructing Global Coherence Representations:Identifying...	17	Experimental	1	TypeScript
209	neelsomani/epistemic-stance-mechinterp Do models distinguish between declared-true and declared-false premises?	16	Experimental	11	Python
210	serre-lab/Lens LENS Project	16	Experimental	52	HTML
211	stchakwdev/NeuroMap Mechanistic interpretability framework for recovering algorithmic structure...	16	Experimental	3	Python
212	Trustworthy-ML-Lab/Linear-Explanations [ICML 24] A novel automated neuron explanation framework that can accurately...	15	Experimental	14	Jupyter Notebook
213	doscsy12/XAI_sentiment_proj Using Explainable Artificial Intelligence (XAI) for sentiment analysis (NLP)	14	Experimental	15	Jupyter Notebook
214	nitin2468git/ml-explainability-toolkit ML model interpretability with SHAP, LIME, and Partial Dependence Plots	14	Experimental	—	Jupyter Notebook
215	Kaushikjas10/Liquefaction-XGBoost-SHAP-Jas-Dodagoudar This repository is associated with interpretable/explainable ML model for...	14	Experimental	5	Jupyter Notebook
216	SMARTDXCLOUD/AI-MHE Meta-machine Learning and Explainable AI: Performance Prediction of Medical...	14	Experimental	—	Python
217	Scontel/ml-model-explainability Tools and techniques for interpreting and explaining machine learning model...	14	Experimental	—	Python
218	andresilvapimentel/RNAtox RNAtox is a code to classify the caspase toxicity and gene knockdown of...	14	Experimental	1	Jupyter Notebook
219	expai-io/expai-tutorials Repository containing sample datasets, models and notebooks to start using EXPAI.	13	Experimental	—	Jupyter Notebook
220	DominiqueMercier/mislabel Code for the paper: Interpreting Deep Models through the Lens of Data	13	Experimental	—	Jupyter Notebook
221	cslab-hub/LocalTSMHAInterpretability Visualization method of MHA which was trained on time series data, to...	13	Experimental	—	TypeScript
222	fanglioc/Compositional_Function_Networks A neural network alternative with interpretability and decent performance	13	Experimental	5	Python
223	xrt11/XAI-CODE XAI-Explaining AI black box models	12	Experimental	8	Python
224	aliciapj/xai-genz Explainable AI & fashion talk & experiments	12	Experimental	5	Jupyter Notebook
225	brendel-group/imi Official repository for the paper "Scale Alone Does not Improve Mechanistic...	12	Experimental	1	JavaScript
226	raaaouf/XAI_for_audio-music_classification This repo contains the code for extracting explainable audio files from...	12	Experimental	8	Jupyter Notebook
227	MarwenSAIDI/WEITA25-Workshops This repo is a collection of all the worshops we did at the WEITA25 for...	11	Experimental	—	Jupyter Notebook
228	RobinU434/AccumulatedLocalEffectPlots This repository is part of the "Fair and Interpretable Machine Learning"...	11	Experimental	—	Jupyter Notebook
229	DominiqueMercier/PatchX Code for the paper: PatchX: Explaining Deep Models by Intelligible Pattern...	11	Experimental	—	Jupyter Notebook
230	Chrysapl/Counterfactual-Explanations counterfactual explanations for ML hyperparameters	11	Experimental	4	Jupyter Notebook
231	DominiqueMercier/Time-to-focus Code for the paper: Time to Focus: A Comprehensive Benchmark Using Time...	11	Experimental	—	Jupyter Notebook
232	Trustworthy-ML-Lab/Audio_Network_Dissection [ICML 24] AND: the first framework to provide automatic natural language...	11	Experimental	4	Jupyter Notebook
233	JayRGopal/Explainable-Deep-Learning-Regularizer A more interpretable way to regularize convolutional neural networks (CNNs)...	11	Experimental	3	Jupyter Notebook
234	CarachinoAlessio/Explainable-AutoML-driven-State-Etimators This repo contains the code of my Master's Thesis. Specifically, it consists...	10	Experimental	2	Jupyter Notebook

Comparisons in this category

shapash and interpret (70 vs 67) imodels and interpret (68 vs 67) shapash and awesome-machine-learning-interpretability (70 vs 62) shapash and AIX360 (70 vs 59) shapash and xai (70 vs 64) xai and AIX360 (64 vs 59)