PN 5: Project Overview

PN 5-1	Optimal Multidimensional Accuracy-Resource Tradeoff
PN 5-2	Data-driven optimisation algorithms for local dynamic model adaptivity
PN 5-2 (II)	Fully-implicit local dynamic model adaptivity with machine-learned scale bridging
PN 5-3	Efficiency Improvements by Code Intrinsic Uncertainty Quantification via Monte Carlo Methods
PN 5-4	Processing uncertain microstructural data
PN 5-6	Physics-informed ANNs for dynamic, distributed and stochastic systems
PN 5-6 (II)	Bayesian, Causal, Universal Differential Equation Learner
PN 5-7	Uncertainty Quantification by Physics- and Data-Based Models for Mechanical Systems
PN 5-8	Exploiting structural knowledge in (nonlinear) PDE problems for efficient deployment of the learning abilities of ANNs
PN 5-8 (II)	Effective uncertainty quantification and ANN dynamics via amplitude equations
PN 5-9	Adaptive and Flexible Macro-Micro Coupling Software
PN 5-9 (II)	Application-Agnostic Software for Model Adaptivity of Two-Scale Coupled Problems
PN 5-10	Bayesian Multiscale Spatio-Temporal Modelling of Extreme Events
PN 5-11	Uncertainty quantification for data-limited inverse problems via efficient probabilistic ML methods
PN 5-12	Machine Physics Learning for spatio-temporal systems: ANN generalization using adaptive grids, domain decomposition and parallelization

PN 5A-1	Analysis of Stochastic Partial Differential Equations and their Efficient Simulation
PN 5A-2	Parameter inference of non-linear subsurface flow in geological carbon dioxide storage: development of adaptive Bayesian sparse2 arbitrary multi-resolution polynomial chaos expansion