Ryan Mohr

Publication Activity (10 Years)

Years Active: 2010-2023
Publications (10 Years): 18

Top Topics

Machine Learning

Top Venues

SIAM J. Sci. Comput.

SIAM J. Appl. Dyn. Syst.

AAAI Spring Symposium: MLPS

Publications

William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
On Equivalent Optimization of Machine Learning Methods. CoRR (2023)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CDC (2022)
William T. Redman, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic
An Operator Theoretic View On Pruning Deep Neural Networks. ICLR (2022)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CoRR (2022)
Ryan Mohr, Maria Fonoberova, Iva Manojlovic, Aleksandr Andrejcuk, Zlatko Drmac, Yannis Kevrekidis, Igor Mezic
Applications of Koopman Mode Analysis to Neural Networks. AAAI Spring Symposium: MLPS (2021)
Ryan Mohr, Allan M. Avila, Soham Ghosh, Ananta Bhattarai, Muqiao Yang, Xintian Feng, Martin Head-Gordon, Ruslan Salakhutdinov, Maria Fonoberova, Igor Mezic
Combining Programmable Potentials and Neural Networks for Materials Problems. AAAI Spring Symposium: MLPS (2021)
Ryan Mohr, Maria Fonoberova, Zlatko Drmac, Iva Manojlovic, Igor Mezic
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression. Entropy 23 (1) (2021)
William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic
An Operator Theoretic Perspective on Pruning Deep Neural Networks. CoRR (2021)
Nithin Govindarajan, Ryan Mohr, Shivkumar Chandrasekaran, Igor Mezic
On the Approximation of Koopman Spectra of Measure-Preserving Flows. SIAM J. Appl. Dyn. Syst. 20 (1) (2021)
Carl Folkestad, Daniel Pastor, Igor Mezic, Ryan Mohr, Maria Fonoberova, Joel Burdick
Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control. ACC (2020)
Zlatko Drmac, Igor Mezic, Ryan Mohr
On Least Squares Problems with Certain Vandermonde-Khatri-Rao Structure with Applications to DMD. SIAM J. Sci. Comput. 42 (5) (2020)
Ryan Mohr, Maria Fonoberova, Zlatko Drmac, Iva Manojlovic, Igor Mezic
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression. CoRR (2020)
Iva Manojlovic, Maria Fonoberova, Ryan Mohr, Aleksandr Andrejcuk, Zlatko Drmac, Yannis Kevrekidis, Igor Mezic
Applications of Koopman Mode Analysis to Neural Networks. CoRR (2020)
Carl Folkestad, Daniel Pastor, Igor Mezic, Ryan Mohr, Maria Fonoberova, Joel Burdick
Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control. CoRR (2019)
Nithin Govindarajan, Ryan Mohr, Shivkumar Chandrasekaran, Igor Mezic
On the Approximation of Koopman Spectra for Measure Preserving Transformations. SIAM J. Appl. Dyn. Syst. 18 (3) (2019)
Zlatko Drmac, Igor Mezic, Ryan Mohr
Data Driven Koopman Spectral Analysis in Vandermonde-Cauchy Form via the DFT: Numerical Method and Theoretical Insights. SIAM J. Sci. Comput. 41 (5) (2019)
Zlatko Drmac, Igor Mezic, Ryan Mohr
On least squares problems with certain Vandermonde-Khatri-Rao structure with applications to DMD. CoRR (2018)
Zlatko Drmac, Igor Mezic, Ryan Mohr
Data Driven Modal Decompositions: Analysis and Enhancements. SIAM J. Sci. Comput. 40 (4) (2018)
Ryan Mohr, Igor Mezic
Searching for Targets of Nonuniform Size Using Mixing Transformations: Constructive Upper Bounds and Limit Laws. J. Nonlinear Sci. 25 (3) (2015)
Ryan Mohr, Igor Mezic
The use of ergodic theory in designing dynamics for search problems. CDC (2010)