Abstract: Multivariate time series anomaly detection (MTSAD) plays a critical role in the Internet of Things (IoT) by identifying malfunctions and attacks. Graph Neural Networks (GNNs) have been ...

Parameter estimation in differential equation models is a critical endeavour in the mathematical modelling of dynamic systems. Such models, represented by ordinary differential equations (ODEs), ...

Abstract: This paper presents a physics-guided machine learning approach that incorporates partial differential equations (PDEs) in a graph neural network model to improve the prediction of water ...

Learn how to create slope fields and sketch the particular solution to a differential equation. Slope fields are tools used ...

Learn how to create slope fields and sketch the particular solution to a differential equation. Slope fields are tools used ...

Building on Graph Neural Controlled Differential Equations, this repository introduces Permutation Equivariant Graph Neural CDEs, which project Graph Neural CDEs onto permutation equivariant function ...

This repository provides the official implementations and experiments for our paper ``Learning Dynamic Graph Embeddings with Neural Controlled Differential Equations''. For the JAX version and ...