1 citations · 1 across the 3 of their papers we have counts for
3 papers
PEtab SciML: an exchange format for specifying and training dynamic scientific machine learning models
Sebastian Persson, Branwen Snelling, Maren Philipps +5
Summary: Dynamic scientific machine learning (SciML) models that combine mechanistic ordinary differential equations (ODEs) with machine learning (ML) components have applications…
Curriculum Multiple Shooting for Robust Training of Neural and Universal Differential Equations
Sebastian Persson, Giacomo Fabrini, Branwen Snelling +1
Neural ordinary differential equations (NODEs) and universal differential equations (UDEs) provide flexible and popular frameworks for learning interpretable dynamical systems from…
Simulation-based inference for stochastic nonlinear mixed-effects models with applications in systems biology
Henrik Häggström, Sebastian Persson, Marija Cvijovic +1
The analysis of data from multiple experiments, such as observations of several individuals, is commonly approached using mixed-effects models, which account for variation between…