4 papers
INDEQS: Informed Neural controlled Differential EQuationS
Michael Detzel, Gabriel Nobis, Kristiyan Blagov +3
Neural Controlled Differential Equations (NCDE) provide a powerful continuous-time framework for forecasting time series, but standard graph-based extensions typically learn spatia…
Fractional Diffusion Bridge Models
Gabriel Nobis, Maximilian Springenberg, Arina Belova +5
We present Fractional Diffusion Bridge Models (FDBM), a novel generative diffusion bridge framework driven by an approximation of the rich and non-Markovian fractional Brownian mot…
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…
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…