Ryan Mohr

According to our database, Ryan Mohr authored at least 16 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Identifying Equivalent Training Dynamics.

William T. Redman, Juan M. Bello-Rivas, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2023

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

2022

An Operator Theoretic View On Pruning Deep Neural Networks.

William T. Redman, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic

Proceedings of the Tenth International Conference on Learning Representations, 2022

Algorithmic (Semi-)Conjugacy via Koopman Operator Theory.

William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic

Proceedings of the 61st IEEE Conference on Decision and Control, 2022

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

Predicting the Critical Number of Layers for Hierarchical Support Vector Regression.

Ryan Mohr, Maria Fonoberova, Zlatko Drmac, Iva Manojlovic, Igor Mezic

Entropy, 2021

An Operator Theoretic Perspective on Pruning Deep Neural Networks.

William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic

CoRR, 2021

Applications of Koopman Mode Analysis to Neural Networks.

Ryan Mohr, Maria Fonoberova, Iva Manojlovic, Aleksandr Andrejcuk, Zlatko Drmac, Yannis G. Kevrekidis, Igor Mezic

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

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

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

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

Extended Dynamic Mode Decomposition with Learned Koopman Eigenfunctions for Prediction and Control.

Carl Folkestad, Daniel Pastor, Igor Mezic, Ryan Mohr, Maria Fonoberova, Joel Burdick

Proceedings of the 2020 American Control Conference, 2020

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

On the Approximation of Koopman Spectra for Measure Preserving Transformations.

Nithin Govindarajan, Ryan Mohr, Shivkumar Chandrasekaran, Igor Mezic

SIAM J. Appl. Dyn. Syst., 2019

2018

Data Driven Modal Decompositions: Analysis and Enhancements.

Zlatko Drmac, Igor Mezic, Ryan Mohr

SIAM J. Sci. Comput., 2018

2015

Searching for Targets of Nonuniform Size Using Mixing Transformations: Constructive Upper Bounds and Limit Laws.

Ryan Mohr, Igor Mezic

J. Nonlinear Sci., 2015

2010

The use of ergodic theory in designing dynamics for search problems.

Ryan Mohr, Igor Mezic

Proceedings of the 49th IEEE Conference on Decision and Control, 2010