QUESADA MOLINA, JOSE PABLO
QUESADA MOLINA, JOSE PABLO
DIPARTIMENTO DI INGEGNERIA CIVILE E AMBIENTALE
A Deep Learning Approach for Polycrystalline Microstructure-Statistical Property Prediction
2021-01-01 Quesada-Molina, J. P.; Mariani, S.
A Deep Learning-Based Approach to Uncertainty Quantification for Polysilicon MEMS
2021-01-01 Quesada-Molina, José Pablo; Mariani, Stefano
A physics-informed neural network approach to stochastic homogenization of polycrystalline materials
2021-01-01 Quesada Molina, J. P.; Mariani, S.
A two-scale multi-physics deep learning model for smart MEMS sensors
2021-01-01 Mariani, S.; Quesada Molina, J. P.
A Two-Scale Multi-Physics Deep Learning Model for Smart MEMS Sensors
2021-01-01 Quesada-Molina, José Pablo; Mariani, Stefano
Deep Learning-based Multiscale Modelling of Polysilicon MEMS
2022-01-01 Quesada-Molina, Jp; Mariani, S
GENERATIVE APPROACH TO MICROSTRUCTURE INFORMATICS FOR RELIABILITY ANALYSIS
2025-01-01 Mehrabi, A.; Quesada Molina, J. P.; Poelma, R. H.; Van Driel, W. D.; Mariani, S.
Hybrid Model-Based and Data-Driven Solution for Uncertainty Quantification at the Microscale
2022-01-01 Quesada-Molina, J. P.; Mariani, S.
Stochastic Homogenization and Uncertainty Quantification: A Data-Driven Approach
2021-01-01 QUESADA MOLINA, JOSE PABLO; Mariani, Stefano
Two-Scale Deep Learning Model for Polysilicon MEMS Sensors
2022-01-01 Quesada-Molina, José Pablo; Mariani, Stefano
Uncertainty Quantification at the Microscale: A Data-Driven Multi-Scale Approach
2022-01-01 Quesada-Molina, J. P.; Mariani, S.