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Search results for explainable ai xai
explainable-ai
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79 search results found
Pytorch Grad Cam
⭐
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.
Aix360
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1,471
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
⭐
856
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
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]
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
Adversarial Explainable Ai
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235
💡 Adversarial attacks on explanations and how to defend them
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
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.
Fastshap
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96
Fast approximate Shapley values in R
Explainableai.jl
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96
Explainable AI in Julia.
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
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)
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
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
⭐
50
Helping AI practitioners better understand their datasets and models in text classification. From ServiceNow.
Xaitk Saliency
⭐
48
An open source, Explainable AI (XAI) framework and toolkit for visual saliency algorithm interfaces and implementations, built for analytics and autonomy applications.
Xplainable
⭐
48
Real-time explainable machine learning for business optimisation
Rise
⭐
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
Ceml
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35
CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
Iprompt
⭐
33
Finding semantically meaningful and accurate prompts.
Yolo Heatmaps
⭐
32
A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).
Mace
⭐
29
Model Agnostic Counterfactual Explanations
Kernelshap
⭐
28
Efficient R implementation of SHAP
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.
Fg Clustering
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26
Explainability for Random Forest Models.
Cem
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26
Repository for our NeurIPS 2022 paper "Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off"
Toybox
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26
The Machine Learning Toybox for testing the behavior of autonomous agents.
Artemis
⭐
19
A Python package with explanation methods for extraction of feature interactions from predictive models
Xrl
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17
Explainable Reinforcement Learning (XRL) Resources
Xai Demonstrator
⭐
17
The XAI Demonstrator is a modular platform that lets users interact with production-grade Explainable AI (XAI) systems.
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).
Xai
⭐
16
Genetic programming method for explaining complex black-box models
Xai Scholar
⭐
16
Cross-field empirical trends analysis of XAI literature
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).
Pipnet
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15
PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)
Pyexplainer
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15
PyExplainer: A Local Rule-Based Model-Agnostic Technique (Explainable AI)
Pyreal
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15
Library for generating human-readable machine learning explanations
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.
Vivo
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13
Variable importance via oscillations
Recourse
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12
Code to reproduce our paper on probabilistic algorithmic recourse: https://arxiv.org/abs/2006.06831
Mindsdb_server
⭐
12
MindsDB server allows you to consume and expose MindsDB workflows, through http.
Hc_ml
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12
Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
Mllp
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12
The code of AAAI 2020 paper "Transparent Classification with Multilayer Logical Perceptrons and Random Binarization".
Article Information 2019
⭐
10
Article for Special Edition of Information: Machine Learning with Python
Slisemap
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9
SLISEMAP: Combining supervised dimensionality reduction with local explanations
Why
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8
Frame-agnostic XAI Library for Computer Vision, for understanding why models behave that way.
Anchorsonr
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8
Implementation of the Anchors algorithm: Explain black-box ML models
Doxpy
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7
Replication package for the KNOSYS paper titled "An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability".
Xai Analytics
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7
XAI-Analytics is a tool that opens the black-box of machine learning. It helps the user to understand the decision-making process of machine learning models.
Teller
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7
Model-agnostic Statistical/Machine Learning explainability (currently Python) for tabular data
Counterfactual Explanation Based On Gradual Construction For Deep Networks
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6
Counterfactual Explanation Based on Gradual Construction for Deep Networks Pytorch
Meme Rnn Xai
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6
MEME: Generating RNN Model Explanations via Model Extraction
Plobelm_1_team_2
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6
AIC XAI 문제 1번 2팀 레파지토리
Tinyshap
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6
Python package providing a minimal implementation of the SHAP algorithm using the Kernel method
Fastcam
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6
A toolkit for efficent computation of saliency maps for explainable AI attribution. This tool was developed at Lawrence Livermore National Laboratory.
Visualime
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5
Implementation of LIME focused on producing user-centric local explanations for image classifiers.
Xi Method
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5
Xi method
Keras Explainable
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5
Efficient explaining AI algorithms for Keras models
Xai
⭐
5
XAI & AI college Recording Repo
Cwox
⭐
5
A XAI Framework to provide Contrastive Whole-output Explanation for Image Classification.
Related Searches
Python Explainable Ai (216)
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