The CPA Journal

Automating Data Analysis with Python Dashboards

In today's data-rich environment, business are always looking for a way to capitalize on available data for new insights and ...
IEEE

Efficient Frequency-Aware k-Core Query on Temporal Graphs

Abstract: In temporal graphs, time and topology are considered to be intertwined. As an evidence, it is observed that the vertices in more cohesive subgraphs have more frequent and more numerous ...
GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
IEEE

FedHeGA: A Federated Learning Framework for Enhanced Node Classification on Heterogeneous Graphs

Abstract: Heterogeneous graph neural networks (HGNNs) have proven effective at capturing complex relationships in graphs with diverse node and edge types. However, centralized training in HGNNs raises ...
GitHub

Multimodal Reasoning with Multimodal Knowledge Graph

To develop the tutorial code, I referred to the repository of the MARS dataset used in the paper: [GitHub] First, as instructed in the README of the MARS repository ...