10 citations · 15 across the 4 of their papers we have counts for
4 papers
Reduced Order Modeling of Partial Differential Equations on Parameter-Dependent Domains Using Deep Neural Networks
Martina Bukač, Iva Manojlović, Boris Muha +1
Partial differential equations (PDEs) are widely used for modeling various physical phenomena. These equations often depend on certain parameters, necessitating either the identifi…
A Koopman Operator-Based Prediction Algorithm and its Application to COVID-19 Pandemic
Igor Mezic, Zlatko Drmac, Nelida Crnjaric-Zic +6
The problem of prediction of behavior of dynamical systems has undergone a paradigm shift in the second half of the 20th century with the discovery of the possibility of chaotic dy…
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression
Ryan Mohr, Maria Fonoberova, Zlatko Drmač +2
Hierarchical support vector regression (HSVR) models a function from data as a linear combination of SVR models at a range of scales, starting at a coarse scale and moving to finer…
Applications of Koopman Mode Analysis to Neural Networks
Iva Manojlović, Maria Fonoberova, Ryan Mohr +4
We consider the training process of a neural network as a dynamical system acting on the high-dimensional weight space. Each epoch is an application of the map induced by the optim…