moDel Agnostic Language for Exploration and eXplanation
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Updated
May 5, 2024 - Python
moDel Agnostic Language for Exploration and eXplanation
A generalized gradient-based CNN visualization technique
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 @ ms8909@nyu.edu
A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI )
Library for multi-dimensional, multi-sensor, uni/multivariate time series data analysis, unsupervised feature selection, unsupervised deep anomaly detection, and prototype of explainable AI for anomaly detector
Visualizing how deep networks make decisions
Compute SHAP values for your tree-based models using the TreeSHAP algorithm
Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
Interesting resources related to Explainable Artificial Intelligence, Interpretable Machine Learning, Interactive Machine Learning, Human in Loop and Visual Analytics.
PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)
Case Study course for DS studies in Summer 2020/2021
Model verification, validation, and error analysis
All about explainable AI, algorithmic fairness and more
A utility for generating heatmaps of YOLOv8 using Layerwise Relevance Propagation (LRP/CRP).
Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks
Deep Insight And Neural Network Analysis
Reading list for "The Shapley Value in Machine Learning" (JCAI 2022)
SIREN: A Simulation Framework for Understanding the Effects of Recommender Systems in Online News Environments
Interpretable Control Exploration and Counterfactual Explanation (ICE) on StyleGAN
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