sissaNassir

lime

Lime: Explaining the predictions of any machine learning classifier

atlas

Apache Atlas

ACNet

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

neural-backed-decision-trees

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

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).

soft-decision-tree

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

xai-series

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

Explainable AI with Python, published by Packt

ProtoTree

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

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)

DJINN

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

Deformable-ProtoPNet

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

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.

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

ABELE

Adversarial Black box Explainer generating Latent Exemplars

GANterfactual

Generating Counterfactual Explanation Images through Generative Adversarial Learning

mprotonet

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

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.

DeDUCE

rdtc

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

fs2od

Filesystem to Onedata

getting-started

A collection of installation scripts for getting started with Onedata.

05-pm

onedata4Sci

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

causalgen

A Causal-based Utility for Data Generation

sap-2023-2024

LocalGlobalPrototypes

onedata-deployments

Examples of Onedata deployments

ProtoTree

prototree experiments with text inputs