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Generate realistic test data in Python fast. No dataset required

Learn the NumPy trick for generating synthetic data that actually behaves like real data.
IEEE

mGNN-bw: Multi-Scale Graph Neural Network Based on Biased Random Walk Path Aggregation for ASD Diagnosis

Abstract: In recent years, computationally assisted diagnosis for classifying autism spectrum disorder (ASD) and typically developing (TD) individuals based on neuroimaging data, such as functional ...
IEEE

Hypergraph Collaborative Filtering With Adaptive Augmentation of Graph Data for Recommendation

Abstract: Self-supervised tasks show significant advantages for node representation learning in recommender systems. This core idea of self-supervised task-based recommender systems depends on data ...
GitHub

GenML: A Python Library to Generate the Mittag-Leffler Correlated Noise

GenML is a Python library designed for generating Mittag-Leffler correlated noise, which is crucial for modeling a wide range of phenomena in complex systems. This document provides a brief overview ...