699 citations · 776 across the 13 of their papers we have counts for
18 papers
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…
Identifying Equivalent Training Dynamics
William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova +3
Study of the nonlinear evolution deep neural network (DNN) parameters undergo during training has uncovered regimes of distinct dynamical behavior. While a detailed understanding o…
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory
William T. Redman, Maria Fonoberova, Ryan Mohr +2
Iterative algorithms are of utmost importance in decision and control. With an ever growing number of algorithms being developed, distributed, and proprietarized, there is a simila…
Koopman Reduced Order Modeling with Confidence Bounds
Ryan Mohr, Maria Fonoberova, Igor Mezic
This paper introduces a reduced order modeling technique based on Koopman operator theory that gives confidence bounds on the model's predictions. It is based on a data-driven spec…
An Operator Theoretic View on Pruning Deep Neural Networks
William T. Redman, Maria Fonoberova, Ryan Mohr +2
The discovery of sparse subnetworks that are able to perform as well as full models has found broad applied and theoretical interest. While many pruning methods have been developed…
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…