30 citations · 30 across the 1 of their papers we have counts for
2 papers
stat.ML2026
Identifiability Guarantees for Drivers and Dynamics of Delayed Physical Systems
Julien Boussard, Antoine Debouchage, Antoine Débouchage +1
A wide range of methods have been proposed, including physics-informed neural networks, which are powerful but do not guarantee identifiability of the dynamics, symbolic regression…
stat.ML2019★ 30 cited
Learning interpretable continuous-time models of latent stochastic dynamical systems
Lea Duncker, Gergo Bohner, Julien Boussard +1
We develop an approach to learn an interpretable semi-parametric model of a latent continuous-time stochastic dynamical system, assuming noisy high-dimensional outputs sampled at u…