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A Reduced Order technique to study bifurcating phenomena: application to the Gross-Pitaevskii equation. SIAM Journal on Scientific Computing [Internet]. 2020 . Available from: https://arxiv.org/abs/1907.07082
. Reduced basis approaches for parametrized bifurcation problems held by non-linear Von Kármán equations. [Internet]. 2019 ;81:112–135. Available from: https://arxiv.org/abs/1804.02014
. A reduced order modeling technique to study bifurcating phenomena: Application to the gross-pitaevskii equation. SIAM Journal on Scientific Computing [Internet]. 2020 . Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096768803&doi=10.1137%2f20M1313106&partnerID=40&md5=47d6012d10854c2f9a04b9737f870592
. Reduced Basis Approaches for Parametrized Bifurcation Problems held by Non-linear Von Kármán Equations. Journal of Scientific Computing [Internet]. 2019 ;81:112-135. Available from: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068973907&doi=10.1007%2fs10915-019-01003-3&partnerID=40&md5=a09af83ce45183d6965cdb79d87a919b
. An artificial neural network approach to bifurcating phenomena in computational fluid dynamics. 2021 .
. Driving bifurcating parametrized nonlinear PDEs by optimal control strategies: application to Navier–Stokes equations with model order reduction. ESAIM: M2AN [Internet]. 2022 ;56(4):1361 - 1400. Available from: https://doi.org/10.1051/m2an/2022044
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