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Maria Fonoberova
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2020 – today
- 2024
- [i8]Tomislav Bazina, Ervin Kamenar, Maria Fonoberova, Igor Mezic:
Koopman-driven grip force prediction through EMG sensing. CoRR abs/2409.17340 (2024) - 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) - [i6]William T. Redman, Dean Huang, Maria Fonoberova, Igor Mezic:
Koopman Learning with Episodic Memory. CoRR abs/2311.12615 (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 - [i5]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
- [j8]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) - [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 - [c2]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 - [i4]William T. Redman
An Operator Theoretic Perspective on Pruning Deep Neural Networks. CoRR abs/2110.14856 (2021) - 2020
- [c1]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 - [i3]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) - [i2]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
- [j7]Igor Mezic
Spectral Complexity of Directed Graphs and Application to Structural Decomposition. Complex. 2019: 9610826:1-9610826:18 (2019) - [i1]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
- [j6]Maria Fonoberova, Vladimir A. Fonoberov, Igor Mezic
Global sensitivity/uncertainty analysis for agent-based models. Reliab. Eng. Syst. Saf. 118: 8-17 (2013) - 2012
- [j5]Maria Fonoberova, Vladimir A. Fonoberov, Igor Mezic
Nonlinear Dynamics of Crime and Violence in Urban Settings. J. Artif. Soc. Soc. Simul. 15(1) (2012)
2000 – 2009
- 2006
- [j4]Dmitrii Lozovanu
Optimal Dynamic Multicommodity Flows in Networks. Electron. Notes Discret. Math. 25: 93-100 (2006) - 2005
- [j3]Maria Fonoberova, Dmitrii Lozovanu:
The minimum cost multicommodity flow problem in dynamic networks and an algorithm for its solving. Comput. Sci. J. Moldova 13(1): 29-36 (2005) - [j2]Maria Fonoberova, Dmitrii Lozovanu:
Game-Theoretic Approach for Solving Multiobjective Flow Problems on Networks. Comput. Sci. J. Moldova 13(2): 168-176 (2005) - 2004
- [j1]Maria Fonoberova, Dmitrii Lozovanu:
The maximum flow in dynamic networks. Comput. Sci. J. Moldova 12(3): 387-396 (2004)
Coauthor Index
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