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Mona Buisson-Fenet
Mona Buisson-Fenet
PhD Student, Mines Paris, Centre Automatique et Systèmes
Verified email at mines-paristech.fr
Title
Cited by
Cited by
Year
Actively learning gaussian process dynamics
M Buisson-Fenet, F Solowjow, S Trimpe
Learning for dynamics and control, 5-15, 2020
782020
Joint state and dynamics estimation with high-gain observers and Gaussian process models
M Buisson-Fenet, V Morgenthaler, S Trimpe, F Di Meglio
2021 American Control Conference (ACC), 4027-4032, 2021
192021
Towards gain tuning for numerical KKL observers
M Buisson-Fenet, L Bahr, V Morgenthaler, F Di Meglio
IFAC-PapersOnLine 56 (2), 4061-4067, 2023
172023
Control of piston position in inviscid gas by bilateral boundary actuation
M Buisson-Fenet, S Koga, M Krstic
2018 IEEE Conference on Decision and Control (CDC), 5622-5627, 2018
162018
Recognition models to learn dynamics from partial observations with neural odes
M Buisson-Fenet, V Morgenthaler, S Trimpe, F Di Meglio
arXiv preprint arXiv:2205.12550, 2022
10*2022
Learning to observe: neural network-based KKL observers
M Buisson-Fenet, L Bahr, FD Meglio
Python toolbox available at https://github. com/Centre-automatique-et …, 2022
72022
Data-Driven Observability Analysis for Nonlinear Stochastic Systems
PF Massiani, M Buisson-Fenet, F Solowjow, F Di Meglio, S Trimpe
IEEE Transactions on Automatic Control, 2023
22023
Experimental data assimilation: learning-based estimation for state-space models
M Buisson-Fenet
Université Paris sciences et lettres, 2023
2023
Towards Gain Tuning for Numerical KKL Observers
V Morgenthaler, F Di Meglio, M Buisson-Fenet, L Bahr
2023
Experimental data assimilation: learning-based estimation for state-space models.(Assimilation de données expérimentales: estimation à base d'apprentissage pour modèles sous …
M Buisson-Fenet
PSL University, Paris, France, 2023
2023
Actively Learning Dynamical Systems with Gaussian Processes
M Buisson-Fenet, F Solowjow, S Trimpe
Mines ParisTech, 2019
2019
Using what you know: Learning dynamics from partial observations with structured neural ODEs
M Buisson-Fenet, V Morgenthaler, S Trimpe, F Di Meglio
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Articles 1–12