m-nauta Goto Github PK

awesome-explainable-ai

A collection of research materials on explainable AI/ML

awesome-machine-learning-interpretability

A curated list of awesome machine learning interpretability resources.

explaining_prototypes

This repository contains code for explaining prototypes learned by ProtoPNet, by quantifying the influence of color hue, shape, texture, contrast and saturation in a prototype

intervene

Interactively Visualizing and Explaining Neural Embeddings

lift

Learning Fault Trees from Observational Data

pipnet

PIP-Net: Patch-based Intuitive Prototypes Network for Interpretable Image Classification (CVPR 2023)

prototree

ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

tcdf

Temporal Causal Discovery Framework (PyTorch): discovering causal relationships between time series

xai-papers

xai_resources

Interesting resources related to XAI (Explainable Artificial Intelligence)