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ORCIDIgor Mezic
- > Home > Persons > Igor Mezic
Publications
- 2023
[i19]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)- [i17]William T. Redman, Dean Huang, Maria Fonoberova, Igor Mezic:
Koopman Learning with Episodic Memory. CoRR abs/2311.12615 (2023) - 2022
- [c50]William T. Redman, Maria Fonoberova, Ryan Mohr, Ioannis G. Kevrekidis, Igor Mezic:
Algorithmic (Semi-)Conjugacy via Koopman Operator Theory. CDC 2022: 6006-6011 - [c49]William T. Redman, Maria Fonoberova, Ryan Mohr, Yannis G. Kevrekidis, Igor Mezic:
An Operator Theoretic View On Pruning Deep Neural Networks. ICLR 2022 - [i14]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
- [j36]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) - [c48]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 - [c47]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 - [c46]Allan M. Avila, Maria Fonoberova, João P. Hespanha, Igor Mezic, Daniel Clymer, Jonathan Goldstein, Marco A. Pravia, Daniel Javorsek:
Game Balancing using Koopman-based Learning. ACC 2021: 710-717 - [i13]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
- [c45]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 - [i11]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) - [i8]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) - 2019
- [j27]Igor Mezic, Vladimir A. Fonoberov, Maria Fonoberova, Tuhin Sahai:
Spectral Complexity of Directed Graphs and Application to Structural Decomposition. Complex. 2019: 9610826:1-9610826:18 (2019) - [i7]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) - 2013
- [j14]Maria Fonoberova, Vladimir A. Fonoberov, Igor Mezic:
Global sensitivity/uncertainty analysis for agent-based models. Reliab. Eng. Syst. Saf. 118: 8-17 (2013) - 2012
- [j12]Maria Fonoberova, Vladimir A. Fonoberov, Igor Mezic, Jadranka Mezic, P. Jeffrey Brantingham:
Nonlinear Dynamics of Crime and Violence in Urban Settings. J. Artif. Soc. Soc. Simul. 15(1) (2012)
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