The use of ergodic theory in designing dynamics for search problems. - Ryan Mohr; Igor Mezic (CDC, 2010)

Searching for Targets of Nonuniform Size Using Mixing Transformations: Constructive Upper Bounds and Limit Laws. - Ryan Mohr; Igor Mezic (J. Nonlinear Sci., 2015)

Data Driven Modal Decompositions: Analysis and Enhancements. - Zlatko Drmac; Igor Mezic; Ryan Mohr (SIAM J. Sci. Comput., 2018)

On the Approximation of Koopman Spectra for Measure Preserving Transformations. - Nithin Govindarajan; Ryan Mohr; Shivkumar Chandrasekaran; Igor Mezic (SIAM J. Appl. Dyn. Syst., 2019)

Data Driven Koopman Spectral Analysis in Vandermonde-Cauchy Form via the DFT: Numerical Method and Theoretical Insights. - Zlatko Drmac; Igor Mezic; Ryan Mohr (SIAM J. Sci. Comput., 2019)

Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control. - Carl Folkestad; Daniel Pastor 001; Igor Mezic; Ryan Mohr; Maria Fonoberova; Joel Burdick (ACC, 2020)

On Least Squares Problems with Certain Vandermonde-Khatri-Rao Structure with Applications to DMD. - Zlatko Drmac; Igor Mezic; Ryan Mohr (SIAM J. Sci. Comput., 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)

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)

On the Approximation of Koopman Spectra of Measure-Preserving Flows. - Nithin Govindarajan; Ryan Mohr; Shivkumar Chandrasekaran; Igor Mezic (SIAM J. Appl. Dyn. Syst., 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)

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

Koopman Reduced-Order Modeling with Confidence Bounds. - Ryan Mohr; Maria Fonoberova; Igor Mezic (SIAM J. Appl. Dyn. Syst., 2025)