sissaNassir

causalgen

A Causal-based Utility for Data Generation

05-pm

lime

Lime: Explaining the predictions of any machine learning classifier

sap-2023-2024

xai-series

mprotonet

MProtoNet: A Case-Based Interpretable Model for Brain Tumor Classification with 3D Multi-parametric Magnetic Resonance Imaging

LocalGlobalPrototypes

onedata4Sci

The Onedata4Sci solution is used to easily register emerging research datasets into the Onedata system, including setting the required data lifecycle parameters.

soft-decision-tree

pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"

fs2od

Filesystem to Onedata

Deformable-ProtoPNet

The official repository for Deformable ProtoPNet, as described in "Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes".

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

getting-started

A collection of installation scripts for getting started with Onedata.

onedata-deployments

Examples of Onedata deployments

ProtoTree

prototree experiments with text inputs

ProtoPNet

This code package implements the prototypical part network (ProtoPNet) from the paper "This Looks Like That: Deep Learning for Interpretable Image Recognition" (to appear at NeurIPS 2019), by Chaofan Chen* (Duke University), Oscar Li* (Duke University), Chaofan Tao (Duke University), Alina Jade Barnett (Duke University), Jonathan Su (MIT Lincoln Laboratory), and Cynthia Rudin (Duke University) (* denotes equal contribution).

rdtc

PyTorch implementation of Learning Decision Trees Recurrently Through Communication (RDTC)

ACNet

ACNet: Strengthening the Kernel Skeletons for Powerful CNN via Asymmetric Convolution Blocks

DJINN

Deep jointly-informed neural networks -- as easy-to-use algorithm for designing/initializing neural nets

atlas

Apache Atlas

ProtoTree

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

neural-backed-decision-trees

Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

How-to-download-ABIDE-Preprocessed-dataset-for-autism-detection

This script automates the download of preprocessed brain imaging data from the ABIDE dataset, focusing on a specific derivative, preprocessing pipeline, and noise-removal strategy. It filters participants by diagnosis (autism or controls) and downloads relevant data, streamlining research on autism spectrum disorder.

edc

Heuristic best-first algorithm for computing Evidence Counterfactuals (SEDC): explaining the model predictions of any classifier using a minimal set of features, such that removing these features results in a predicted class change.

GANterfactual

Generating Counterfactual Explanation Images through Generative Adversarial Learning

DeDUCE

ABELE

Adversarial Black box Explainer generating Latent Exemplars

PIPNet

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

interpretable-ai-book

Code associated with my Interpretable AI Book (https://www.manning.com/books/interpretable-ai)

Hands-On-Explainable-AI-XAI-with-Python

Explainable AI with Python, published by Packt