moDel Agnostic Language for Exploration and eXplanation
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Updated
Jun 9, 2024 - Python
moDel Agnostic Language for Exploration and eXplanation
A Python package implementing a new interpretable machine learning model for text classification (with visualization tools for Explainable AI )
A generalized gradient-based CNN visualization technique
An Open-Source Library for the interpretability of time series classifiers
TalkToModel gives anyone with the powers of XAI through natural language conversations 💬!
This Repo containes the implemnetation of generating Guided-GradCAM for 3D medical Imaging using Nifti file in tensorflow 2.0. Different input files can be used in that case need to edit the input to the Guided-gradCAM model.
Application of the LIME algorithm by Marco Tulio Ribeiro, Sameer Singh, Carlos Guestrin to the domain of time series classification
PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)
Moore Machine Networks (MMN): Learning Finite-State Representations of Recurrent Policy Networks
Classification and Object Detection XAI methods (CAM-based, backpropagation-based, perturbation-based, statistic-based) for thyroid cancer ultrasound images
SIREN: A Simulation Framework for Understanding the Effects of Recommender Systems in Online News Environments
ProtoPFormer: Concentrating on Prototypical Parts in Vision Transformers for Interpretable Image Recognition
Local interpretability for survival models
Concept activation vectors for Keras
XRouting: An explainable vehicle rerouting system based on reinforcement learning with transformer structure
📺 A Python library for pruning and visualizing Keras Neural Networks' structure and weights
A Deepfake detector based on hybrid EfficientNet CNN and Vision Transformer archietcture. The model is explainable by rendering a heatmap visualization of the Transformer Relevancy / Attention map.
Explanations in Multi-Model Planning
A library that helps to explain AI models in a really quick & easy way
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