4 papers
INDEQS: Informed Neural controlled Differential EQuationS
Michael Detzel, Gabriel Nobis, Kristiyan Blagov +4
Neural Controlled Differential Equations (NCDE) provide a powerful continuous-time framework for forecasting time series, but standard graph-based extensions typically learn spatia…
Synthetic Datasets for Machine Learning on Spatio-Temporal Graphs using PDEs
Jost Arndt, Utku Isil, Michael Detzel +2
Many physical processes can be expressed through partial differential equations (PDEs). Real-world measurements of such processes are often collected at irregularly distributed poi…
Spatial Shortcuts in Graph Neural Controlled Differential Equations
Michael Detzel, Gabriel Nobis, Jackie Ma +1
We incorporate prior graph topology information into a Neural Controlled Differential Equation (NCDE) to predict the future states of a dynamical system defined on a graph. The inf…
Generative Fractional Diffusion Models
Gabriel Nobis, Maximilian Springenberg, Marco Aversa +11
We introduce the first continuous-time score-based generative model that leverages fractional diffusion processes for its underlying dynamics. Although diffusion models have excell…