Publikationen der FOR 5339

Hier finden Sie die Publikationen der FOR 5339, welche mit Unterstützung der DFG im Laufe der Projektes veröffentlicht wurden.


Titel	Autor	Quelle
Physics-informed neural networks for data-free surrogate modelling and engineering optimization – An example from composite manufacturing	Tobias Würth, Constantin Krauß, Clemens Zimmerling, Luise Kärger	Materials & Design, Volume 231, July 2023, 112034 Physics-informed neural networks for data-free surrogate modelling and engineering optimization
GROUNDING GRAPH NETWORK SIMULATORS USING PHYSICAL SENSOR OBSERVATIONS	Jonas Linkerhägner, Niklas Freymuth, Paul Maria Scheikl, Franziska Mathis-Ullrich, Gerhard Neumann,	ICLR 2023, GROUNDING GRAPH NETWORK SIMULATORS USING PHYSICAL SENSOR OBSERVATIONS
Towards Representing Processes and Reasoning with Process Descriptions on the Web	Andreas Harth, Tobias Käfer, Anisa Rula, Jean-Paul	Towards Representing Processes and Reasoning with Process Descriptions on the Web
Latent Task-Specific Graph Network Simulators	Philipp Dahlinger, Niklas Freymuth, Michael Volpp, Tai Hoang, Gerhard Neumann	NeurIPS 2023 AI for Science Workshop, Latent Task-Specific Graph Network Simulators
Multi-target regression and cross-validation for non-isothermal glass molding experiments with small sample sizes	Hendrik Mende, Saksham Kiroriwal, Julius Pfrommer, Robert H. Schmitt, Jürgen Beyerer	SPIE Optifab, 2023, Rochester, New York, United States Multi-target regression and cross-validation for non-isothermal glass molding experiments with small sample sizes
Adaptive Swarm Mesh Refinement	Niklas Freymuth, Philipp Dahlinger, Tobias Würth, Simon Reisch, Luise Kärger, Gerhard Neumann	NeurIPS 2023, Adaptive Swarm Mesh Refinement