9 citations · 9 across the 5 of their papers we have counts for
5 papers
Fast Karhunen-Loève Expansions via FFT-Accelerated Toeplitz Operators
Nils Wildt, Wolfgang Nowak
Gaussian random fields are a versatile tool used in the fields of stochastic PDEs, uncertainty quantification, and geostatistical simulation. One way to obtain them is to use a tru…
CODE: A global approach to ODE dynamics learning
Nils Wildt, Daniel M. Tartakovsky, Sergey Oladyshkin +1
Ordinary differential equations (ODEs) are a conventional way to describe the observed dynamics of physical systems. Scientists typically hypothesize about dynamical behavior, prop…
Inferring Underwater Topography with FINN
Coşku Can Horuz, Matthias Karlbauer, Timothy Praditia +3
Spatiotemporal partial differential equations (PDEs) find extensive application across various scientific and engineering fields. While numerous models have emerged from both physi…
Overdispersion in gate tomography: Experiments and continuous, two-scale random walk model on the Bloch sphere
Wolfgang Nowak, Tim Brünnette, Merel Schalkers +1
Noisy intermediate-scale quantum computers (NISQ) are in their childhood, but showing high promise. One main concern for NISQ machines is their inherent noisiness, as the qubit sta…
The Deep Arbitrary Polynomial Chaos Neural Network or how Deep Artificial Neural Networks could benefit from Data-Driven Homogeneous Chaos Theory
Sergey Oladyshkin, Timothy Praditia, Ilja Kröker +3
Artificial Intelligence and Machine learning have been widely used in various fields of mathematical computing, physical modeling, computational science, communication science, and…