Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
-
Updated
Jul 18, 2024 - Python
Quickly build Explainable AI dashboards that show the inner workings of so-called "blackbox" machine learning models.
Home for explainer documents originated by the Microsoft Edge team
Interpret Community extends Interpret repository with additional interpretability techniques and utility functions to handle real-world datasets and workflows.
A library that incorporates state-of-the-art explainers for text-based machine learning models and visualizes the result with a built-in dashboard.
Explanation method for Graph Neural Networks (GNNs)
Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
An interactive exploration of various number formats
Different approaches to solving coding challenges, along with explanations of the thinking involved.
A LIME explainer app for fine-grained sentiment classification, written using Streamlit.
A small explainer repository that shows how to use the BEM syntax in CSS.
Bachelor Thesis about using attention for explaining a deep learning AI model in computer vision
SudokuNCExplainer is my modifications to SudokuExplainer to also solve (and rate) Non-Consecutive sudokus (SudokuNC).
画像の分類とモデルの説明性を可視化します。
Implementation of Model-Agnostic Graph Explainability Technique from Scratch in PyTorch
Add a description, image, and links to the explainer topic page so that developers can more easily learn about it.
To associate your repository with the explainer topic, visit your repo's landing page and select "manage topics."