Ryan Mohr

22 papers A* 2C 1Journal 15Unranked 4
YearRankTypeTitle / Venue / Authors
2025 J jnl
Koopman Reduced-Order Modeling with Confidence Bounds.
SIAM J. Appl. Dyn. Syst.
Ryan Mohr, Maria Fonoberova, Igor Mezic
2024 A* conf
Identifying Equivalent Training Dynamics.
NeurIPS
William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic
2023 J jnl
On Equivalent Optimization of Machine Learning Methods.
CoRR
William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
2022 — conf
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory.
CDC
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
2022 J jnl
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory.
CoRR
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
2022 A* conf
An Operator Theoretic View On Pruning Deep Neural Networks.
ICLR
William T. Redman, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic
2021 J jnl
An Operator Theoretic Perspective on Pruning Deep Neural Networks.
CoRR
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
2021 — conf
Applications of Koopman Mode Analysis to Neural Networks.
AAAI Spring Symposium: MLPS
Ryan Mohr, Maria Fonoberova, Iva Manojlovic, Aleksandr Andrejcuk, Zlatko Drmac, Yannis G. Kevrekidis, Igor Mezic
2021 — conf
Combining Programmable Potentials and Neural Networks for Materials Problems.
AAAI Spring Symposium: MLPS
Ryan Mohr, Allan M. Avila, Soham Ghosh, Ananta Bhattarai, Muqiao Yang, Xintian Feng, Martin Head-Gordon, Ruslan Salakhutdinov, Maria Fonoberova, Igor Mezic
2021 J jnl
On the Approximation of Koopman Spectra of Measure-Preserving Flows.
SIAM J. Appl. Dyn. Syst.
Nithin Govindarajan, Ryan Mohr, Shivkumar Chandrasekaran, Igor Mezic
2021 J jnl
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression.
Entropy
Ryan Mohr, Maria Fonoberova, Zlatko Drmac, Iva Manojlovic, Igor Mezic
2020 J jnl
Applications of Koopman Mode Analysis to Neural Networks.
CoRR
Iva Manojlovic, Maria Fonoberova, Ryan Mohr, Aleksandr Andrejcuk, Zlatko Drmac, Yannis G. Kevrekidis, Igor Mezic
2020 C conf
Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control.
ACC
Carl Folkestad, Daniel Pastor, Igor Mezic, Ryan Mohr, Maria Fonoberova, Joel Burdick
2020 J jnl
On Least Squares Problems with Certain Vandermonde-Khatri-Rao Structure with Applications to DMD.
SIAM J. Sci. Comput.
Zlatko Drmac, Igor Mezic, Ryan Mohr
2020 J jnl
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression.
CoRR
Ryan Mohr, Maria Fonoberova, Zlatko Drmac, Iva Manojlovic, Igor Mezic
2019 J jnl
Data Driven Koopman Spectral Analysis in Vandermonde-Cauchy Form via the DFT: Numerical Method and Theoretical Insights.
SIAM J. Sci. Comput.
Zlatko Drmac, Igor Mezic, Ryan Mohr
2019 J jnl
Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control.
CoRR
Carl Folkestad, Daniel Pastor, Igor Mezic, Ryan Mohr, Maria Fonoberova, Joel Burdick
2019 J jnl
On the Approximation of Koopman Spectra for Measure Preserving Transformations.
SIAM J. Appl. Dyn. Syst.
Nithin Govindarajan, Ryan Mohr, Shivkumar Chandrasekaran, Igor Mezic
2018 J jnl
Data Driven Modal Decompositions: Analysis and Enhancements.
SIAM J. Sci. Comput.
Zlatko Drmac, Igor Mezic, Ryan Mohr
2018 J jnl
On least squares problems with certain Vandermonde-Khatri-Rao structure with applications to DMD.
CoRR
Zlatko Drmac, Igor Mezic, Ryan Mohr
2015 J jnl
Searching for Targets of Nonuniform Size Using Mixing Transformations: Constructive Upper Bounds and Limit Laws.
J. Nonlinear Sci.
Ryan Mohr, Igor Mezic
2010 — conf
The use of ergodic theory in designing dynamics for search problems.
CDC
Ryan Mohr, Igor Mezic