1 to 10 of 10 Results
Mar 28, 2025
Spatiotemporal ensembles often result from physical simulations. These ensembles contain many information-rich members, each corresponding to different simulation input parameters. The extensive data size makes manual analysis infeasible, necessitating automated approaches to assist the analysis. In the preceding project (PN 6-8 (I)), methods and t... |
Nov 20, 2024
This Dataverse contains replication data and visualizations from Project Network 6-15: Machine Learning and Reservoir Computing with Many-Body Dynamics. The project is part of SimTech’s Project Network 6, Machine Learning for Simulation (https://www.simtech.uni-stuttgart.de/exc/research/pn/pn6/ ). The Dataverse includes simulations of non-equilibri... |
Jul 3, 2024
SimTech Project PN 6-5 (II) "Interpretable and explainable cognitive inspired machine learning systems" |
Mar 8, 2024
Advanced learning strategies for potential energy surfaces applied to organic electrolytes |
Mar 8, 2024
Unified diagnostic evaluation of physics-based, data-driven and hybrid hydrological models based on information theory |
May 17, 2023
Meta-Uncertainty represents a fully probabilistic framework for quantifying the uncertainty over Bayesian posterior model probabilities (PMPs) using meta-models. Meta-models integrate simulated and observed data into a predictive distribution for new PMPs and help reduce overconfidence and estimate the PMPs in future replication studies. |
Sep 29, 2021
SimTech Project PN 6-6 "Machine Learning for Data-driven Visualization" |
Mar 16, 2021
SimTech Project PN6-3 "Understanding Physical Constraints in Machine Learning for Simulation" |
Oct 27, 2020
SimTech Project PN 6-4 "Visual Analytics for Deep Learning" |