The maximum flow in dynamic networks. - Maria Fonoberova; Dmitrii Lozovanu (Comput. Sci. J. Moldova, 2004)

The minimum cost multicommodity flow problem in dynamic networks and an algorithm for its solving. - Maria Fonoberova; Dmitrii Lozovanu (Comput. Sci. J. Moldova, 2005)

Game-Theoretic Approach for Solving Multiobjective Flow Problems on Networks. - Maria Fonoberova; Dmitrii Lozovanu (Comput. Sci. J. Moldova, 2005)

Optimal Dynamic Multicommodity Flows in Networks. - Dmitrii Lozovanu; Maria Fonoberova (Electron. Notes Discret. Math., 2006)

Nonlinear Dynamics of Crime and Violence in Urban Settings. - Maria Fonoberova; Vladimir A. Fonoberov; Igor Mezic; Jadranka Mezic; P. Jeffrey Brantingham (J. Artif. Soc. Soc. Simul., 2012)

Global sensitivity/uncertainty analysis for agent-based models. - Maria Fonoberova; Vladimir A. Fonoberov; Igor Mezic (Reliab. Eng. Syst. Saf., 2013)

Spectral Complexity of Directed Graphs and Application to Structural Decomposition. - Igor Mezic; Vladimir A. Fonoberov; Maria Fonoberova; Tuhin Sahai (Complex., 2019)

Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control. - Carl Folkestad; Daniel Pastor; Igor Mezic; Ryan Mohr; Maria Fonoberova; Joel Burdick (ACC, 2020)

Combining Programmable Potentials and Neural Networks for Materials Problems. - Ryan Mohr; Allan M. Avila; Soham Ghosh; Ananta Bhattarai; Muqiao Yang; Xintian Feng; Martin Head-Gordon; Ruslan Salakhutdinov; Maria Fonoberova; Igor Mezic (AAAI Spring Symposium: MLPS, 2021)

Applications of Koopman Mode Analysis to Neural Networks. - Ryan Mohr; Maria Fonoberova; Iva Manojlovic; Aleksandr Andrejcuk; Zlatko Drmac; Yannis G. Kevrekidis; Igor Mezic (AAAI Spring Symposium: MLPS, 2021)

Game Balancing using Koopman-based Learning. - Allan M. Avila; Maria Fonoberova; João P. Hespanha 001; Igor Mezic; Daniel Clymer; Jonathan Goldstein; Marco A. Pravia; Daniel Javorsek (ACC, 2021)

An Operator Theoretic Perspective on Pruning Deep Neural Networks. - William T. Redman; Maria Fonoberova; Ryan Mohr; Ioannis G. Kevrekidis; Igor Mezic (CoRR, 2021)

Predicting the Critical Number of Layers for Hierarchical Support Vector Regression. - Ryan Mohr; Maria Fonoberova; Zlatko Drmac; Iva Manojlovic; Igor Mezic (Entropy, 2021)

Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. - William T. Redman; Maria Fonoberova; Ryan Mohr; Ioannis G. Kevrekidis; Igor Mezic (CDC, 2022)

An Operator Theoretic View On Pruning Deep Neural Networks. - William T. Redman; Maria Fonoberova; Ryan Mohr; Yannis G. Kevrekidis; Igor Mezic (ICLR, 2022)

On Equivalent Optimization of Machine Learning Methods. - William T. Redman; Juan M. Bello-Rivas; Maria Fonoberova; Ryan Mohr; Ioannis G. Kevrekidis; Igor Mezic (CoRR, 2023)

Koopman Learning with Episodic Memory. - William T. Redman; Dean Huang; Maria Fonoberova; Igor Mezic (CoRR, 2023)

Identifying Equivalent Training Dynamics. - William T. Redman; Juan M. Bello-Rivas; Maria Fonoberova; Ryan Mohr; Yannis G. Kevrekidis; Igor Mezic (NeurIPS, 2024)

Koopman-driven grip force prediction through EMG sensing. - Tomislav Bazina; Ervin Kamenar; Maria Fonoberova; Igor Mezic (CoRR, 2024)