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2020 – today
- 2023
[i7]William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
On Equivalent Optimization of Machine Learning Methods. CoRR abs/2302.09160 (2023)- 2022
- [c6]William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CDC 2022: 6006-6011 - [c5]William T. Redman, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic:
An Operator Theoretic View On Pruning Deep Neural Networks. ICLR 2022 - [i6]William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CoRR abs/2209.06374 (2022) - 2021
- [j7]Ryan Mohr, Maria Fonoberova
, Zlatko Drmac, Iva Manojlovic, Igor Mezic:
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression. Entropy 23(1): 37 (2021) - [j6]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): 232-261 (2021) - [c4]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 - [c3]Ryan Mohr, Maria Fonoberova, Iva Manojlovic, Aleksandr Andrejcuk, Zlatko Drmac, Yannis G. Kevrekidis, Igor Mezic:
Applications of Koopman Mode Analysis to Neural Networks. AAAI Spring Symposium: MLPS 2021 - [i5]William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
An Operator Theoretic Perspective on Pruning Deep Neural Networks. CoRR abs/2110.14856 (2021) - 2020
- [j5]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): A3250-A3284 (2020) - [c2]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: 3906-3913 - [i4]Iva Manojlovic, Maria Fonoberova, Ryan Mohr, Aleksandr Andrejcuk, Zlatko Drmac, Yannis G. Kevrekidis, Igor Mezic:
Applications of Koopman Mode Analysis to Neural Networks. CoRR abs/2006.11765 (2020) - [i3]Ryan Mohr, Maria Fonoberova, Zlatko Drmac, Iva Manojlovic, Igor Mezic:
Predicting the Critical Number of Layers for Hierarchical Support Vector Regression. CoRR abs/2012.11734 (2020)
2010 – 2019
- 2019
- [j4]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): 1454-1497 (2019) - [j3]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): A3118-A3151 (2019) - [i2]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 abs/1911.08751 (2019) - 2018
- [j2]Zlatko Drmac, Igor Mezic, Ryan Mohr:
Data Driven Modal Decompositions: Analysis and Enhancements. SIAM J. Sci. Comput. 40(4): A2253-A2285 (2018) - [i1]Zlatko Drmac, Igor Mezic, Ryan Mohr:
On least squares problems with certain Vandermonde-Khatri-Rao structure with applications to DMD. CoRR abs/1811.12562 (2018) - 2015
- [j1]Ryan Mohr, Igor Mezic:
Searching for Targets of Nonuniform Size Using Mixing Transformations: Constructive Upper Bounds and Limit Laws. J. Nonlinear Sci. 25(3): 741-777 (2015) - 2010
- [c1]Ryan Mohr, Igor Mezic:
The use of ergodic theory in designing dynamics for search problems. CDC 2010: 7300-7307
Coauthor Index
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