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GraphToolbox: A Configurable Python Framework for Graph Neural Network Forecasting
Electricity forecasting often involves spatially related signals observed over regions, substations, and feeders, and Graph Neural Networks (GNNs) provide a natural way to represent these relations. Building a complete GNN forecasting experiment is nonetheless laborious, because graph construction, model selection, training, aggregation, and interpretation sit in incompatible tools. We present GraphToolbox, an open-source Python framework that unifies these stages in one configurationdriven pipeline built on PyTorch Geometric. It offers data-driven graph construction, an adapter that instantia
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- arXiv · AI, language, vision and robotics · 2026-09-21T13:58:35.000Z
First collected: 2026-09-23T06:11:12.848Z. This is not the publication date.