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154 search results found
Pytorch Grad Cam
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8,723
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Interpret
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5,992
Fit interpretable models. Explain blackbox machine learning.
Awesome Machine Learning Interpretability
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3,241
A curated list of awesome responsible machine learning resources.
Alibi
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2,257
Algorithms for explaining machine learning models
Explainerdashboard
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2,118
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
Aix360
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1,533
Interpretability and explainability of data and machine learning models
Dice
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1,257
Generate Diverse Counterfactual Explanations for any machine learning model.
Dalex
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1,242
moDel Agnostic Language for Exploration and eXplanation
Awesome Explainable Ai
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1,208
A collection of research materials on explainable AI/ML
Xai
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1,060
XAI - An eXplainability toolbox for machine learning
Awesome Interpretable Machine Learning
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856
Xai_resources
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634
Interesting resources related to XAI (Explainable Artificial Intelligence)
Interpretable_machine_learning_with_python
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629
Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.
Xplique
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522
👋 Xplique is a Neural Networks Explainability Toolbox
Awesome Graph Explainability Papers
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486
Papers about explainability of GNNs
Quantus
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460
Quantus is an eXplainable AI toolkit for responsible evaluation of neural network explanations
Mli Resources
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405
H2O.ai Machine Learning Interpretability Resources
Explainx
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375
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]
Pyss3
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307
A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI :octocat:)
Modelstudio
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305
📍 Interactive Studio for Explanatory Model Analysis
Tf Keras Vis
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286
Neural network visualization toolkit for tf.keras
Awesome Fairness In Ai
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257
A curated list of awesome Fairness in AI resources
Adversarial Explainable Ai
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235
💡 Adversarial attacks on explanations and how to defend them
Fcdd
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204
Repository for the Explainable Deep One-Class Classification paper
Whitebox
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184
[Not Actively Maintained] Whitebox is an open source E2E ML monitoring platform with edge capabilities that plays nicely with kubernetes
Ema
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156
Explanatory Model Analysis. Explore, Explain and Examine Predictive Models
Zennit
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151
Zennit is a high-level framework in Python using PyTorch for explaining/exploring neural networks using attribution methods like LRP.
Gnnlens2
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136
Visualization tool for Graph Neural Networks
Visual Attribution
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117
Pytorch Implementation of recent visual attribution methods for model interpretability
Lrp_for_lstm
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115
Layer-wise Relevance Propagation (LRP) for LSTMs
Gsat
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111
[ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
Covidnet Ct
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108
COVID-Net Open Source Initiative - Models and Data for COVID-19 Detection in Chest CT
Fastshap
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96
Fast approximate Shapley values in R
Explainableai.jl
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96
Explainable AI in Julia.
Breakdown
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87
Model Agnostics breakDown plots
Rrl
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82
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"
Cade
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81
Code for our USENIX Security 2021 paper -- CADE: Detecting and Explaining Concept Drift Samples for Security Applications
Ibreakdown
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79
Break Down with interactions for local explanations (SHAP, BreakDown, iBreakDown)
Survex
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79
Explainable Machine Learning in Survival Analysis
Treeshap
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72
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
Ml Fairness Framework
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68
FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)
Talktomodel
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68
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
Survshap
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65
SurvSHAP(t): Time-dependent explanations of machine learning survival models
Awesome Shapley Value
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63
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
Da_visualization
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62
[CVPR2021] "Visualizing Adapted Knowledge in Domain Transfer". Visualization for domain adaptation. #explainable-ai
Imodelsx
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60
Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.
Adaptive Wavelets
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60
Adaptive, interpretable wavelets across domains (NeurIPS 2021)
Auditor
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59
Model verification, validation, and error analysis
Expmrc
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59
ExpMRC: Explainability Evaluation for Machine Reading Comprehension
Shapviz
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57
R package for SHAP plots
Azimuth
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50
Helping AI practitioners better understand their datasets and models in text classification. From ServiceNow.
Xai Iml Sota
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50
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
Xaitk Saliency
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48
An open source, Explainable AI (XAI) framework and toolkit for visual saliency algorithm interfaces and implementations, built for analytics and autonomy applications.
Xplainable
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48
Real-time explainable machine learning for business optimisation
Rise
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44
Detect model's attention
Logic_explained_networks
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43
Logic Explained Networks is a python repository implementing explainable-by-design deep learning models.
Torchprism
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40
Principal Image Sections Mapping. Convolutional Neural Network Visualisation and Explanation Framework
Visual Correspondence Xai
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38
Official code for NeurIPS 2022 paper https://arxiv.org/abs/2208.00780 Visual correspondence-based explanations improve AI robustness and human-AI team accuracy
Concept Based Xai
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37
Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
Live
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35
Local Interpretable (Model-agnostic) Visual Explanations - model visualization for regression problems and tabular data based on LIME method. Available on CRAN
Ceml
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35
CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
Iprompt
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33
Finding semantically meaningful and accurate prompts.
Sentimenter_minimal_hai
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33
Minimal starting point for rapid prototyping interactive Human-AI tools
Yolo Heatmaps
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32
A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).
Xai Tutorials
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31
Self-explanatory tutorials for different model-agnostic and model-specific XAI methods
Mindsdb_native
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29
Machine Learning in one line of code
Arenar
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29
Data generator for Arena - interactive XAI dashboard
Mace
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29
Model Agnostic Counterfactual Explanations
Kernelshap
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28
Efficient R implementation of SHAP
Rsafe
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28
Surrogate Assisted Feature Extraction in R
Toybox
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26
The Machine Learning Toybox for testing the behavior of autonomous agents.
Automated Explanations
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26
Explain a black-box module in natural language.
Fg Clustering
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26
Explainability for Random Forest Models.
Awesomeresponsibleai
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26
A curated list of awesome academic research, books, code of ethics, data sets, institutes, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible AI and Human-Centered AI.
Cem
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26
Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off"
Flashlight
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20
Machine learning explanations
Contrxt
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19
a tool for comparing the predictions of any text classifiers
Hstats
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19
Friedman's H-statistics
Diabetes_use_case
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19
Sample use case for Xavier AI in Healthcare conference: https://www.xavierhealth.org/ai-summit-day2/
Artemis
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19
A Python package with explanation methods for extraction of feature interactions from predictive models
Ai_book
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17
AI book for everyone
Agrum
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17
This repository is a mirror. If you want to raise an issue or contact us, we encourage you to do it on Gitlab (https://gitlab.com/agrumery/aGrUM).
Interpretable Ml
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17
Techniques & resources for training interpretable ML models, explaining ML models, and debugging ML models.
Xai Demonstrator
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17
The XAI Demonstrator is a modular platform that lets users interact with production-grade Explainable AI (XAI) systems.
Awesome Lists Machine Learning
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17
A curated list of awesome lists on Machine Learning.
Pyxai
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17
PyXAI (Python eXplainable AI) is a Python library (version 3.6 or later) allowing to bring formal explanations suited to (regression or classification) tree-based ML models (Decision Trees, Random Forests, Boosted Trees, ...).
Xrl
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17
Explainable Reinforcement Learning (XRL) Resources
Hint
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17
[CVPR 2022] HINT: Hierarchical Neuron Concept Explainer
Arena
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17
Interactive XAI dashboard
Xai
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16
Genetic programming method for explaining complex black-box models
Dlime_experiments
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16
In this work, we propose a deterministic version of Local Interpretable Model Agnostic Explanations (LIME) and the experimental results on three different medical datasets shows the superiority for Deterministic Local Interpretable Model-Agnostic Explanations (DLIME).
Xai Scholar
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16
Cross-field empirical trends analysis of XAI literature
Xai Tool4gee
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16
A Colab notebook for land cover mapping and monitoring using Earth Engine
Ablation
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15
Evaluating XAI methods through ablation studies.
Pyreal
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15
Library for generating human-readable machine learning explanations
Pyexplainer
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15
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
Lri
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15
[ICLR 2023] Learnable Randomness Injection (LRI) for interpretable Geometric Deep Learning.
Pipnet
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15
PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)
Remembering For The Right Reasons
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14
Official Implementation of Remembering for the Right Reasons (ICLR 2021)
Merlin
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14
MERLIN is a global, model-agnostic, contrastive explainer for any tabular or text classifier. It provides contrastive explanations of how the behaviour of two machine learning models differs.
1-100 of 154 search results
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