9 citations · 9 across the 3 of their papers we have counts for
4 papers
Neural Spline Flow Diffeomorphisms for Pullback Finite Element Methods on Complex Domains
Ioannis Kalogeris, Anaksagoras Spitas, Konstantinos Atzarakis +2
We propose a method for solving partial differential equations on complex domains by learning smooth, invertible mappings from a fixed reference domain using Neural Spline Flows (N…
AI-enhanced iterative solvers for accelerating the solution of large scale parametrized systems
Stefanos Nikolopoulos, Ioannis Kalogeris, Vissarion Papadopoulos +1
Recent advances in the field of machine learning open a new era in high performance computing. Applications of machine learning algorithms for the development of accurate and cost-…
Interval and fuzzy physics-informed neural networks for uncertain fields
Jan Niklas Fuhg, Ioannis Kalogeris, Amélie Fau +1
Temporally and spatially dependent uncertain parameters are regularly encountered in engineering applications. Commonly these uncertainties are accounted for using random fields an…
Non-intrusive Surrogate Modeling for Parametrized Time-dependent PDEs using Convolutional Autoencoders
Stefanos Nikolopoulos, Ioannis Kalogeris, Vissarion Papadopoulos
This work presents a non-intrusive surrogate modeling scheme based on machine learning technology for predictive modeling of complex systems, described by parametrized time-depende…