1 citations · 1 across the 4 of their papers we have counts for
5 papers
Robust Importance Sampling for Rare Events via Constrained Gaussian Mixtures
Paweł Lorek, Rafał Nowak, Rafał Topolnicki +2
We study estimating rare-event probabilities with and general $g : \mathbb{R}^d \to \m…
Transferable 3D Convolutional Neural Networks for Elastic Constants Prediction in Nanoporous Metals
Sergei Zorkaltsev, Rafał Topolnicki, Tal-El Carmon +4
The topology of nanoporous metals is crucial for determining their mechanical response. In this work, we generated 6,000 gold and 422 silver nanoporous structures and calculated th…
Physics-informed convolutional neural networks for fluid flow through porous media
Rafał Topolnicki, Paweł Dłotko, Maciej Matyka
Accurate simulation of fluid flow in porous media is challenging due to complex pore-space geometries and the computational cost of solving the Navier-Stokes equations. This diffic…
Direction-aware topological descriptors for elastic stiffness tensor prediction in porous materials
Rafał Topolnicki, Michał Bogdan, Jakub Malinowski +3
Classical topological descriptors used in topological data analysis (TDA) are invariant under permutations of spatial axes and therefore cannot represent the loading direction, whi…
Reducing Estimation Uncertainty Using Normalizing Flows and Stratification
Paweł Lorek, Rafał Nowak, Rafał Topolnicki +3
Estimating the expectation of a real-valued function of a random variable from sample data is a critical aspect of statistical analysis, with far-reaching implications in various a…