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- 2022
- Bi-objective Bayesian optimization of engineering problems with cheap and expensive cost functions (2022) ENGINEERING WITH COMPUTERS.
- Satellite based fault diagnosis of photovoltaic systems using recurrent neural networks (2022) APPLIED ENERGY. 305.
- Frequency domain behavior of S‐parameters piecewise‐linear fitting in a digital‐wave framework (2022) INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS. 35(1).
- Adaptive sampling with automatic stopping for feasible region identification in engineering design (2022) ENGINEERING WITH COMPUTERS.
- 2021
- Chapter 10 : Mixed epistemic-aleatory uncertainty using a new polynomial chaos formulation combined with machine learning (2021) Uncertainty quantification of electromagnetic devices, circuits, and systems. p.243-262
- Complex vector fitting toolbox : a software package for the modelling and simulation of general linear and passive baseband systems (2021) ELECTRONICS LETTERS. 57(10). p.404-406
- Temporal convolutional networks for fault diagnosis of photovoltaic systems using satellite and inverter measurements (2021) BuildSys 2021, the 8th ACM International Conference on Systems for Energy-Efficient Buildings, Cities and Transportation, Proceedings. p.180-183
- Bayesian active learning for multi-objective feasible region identification in microwave devices (2021) ELECTRONICS LETTERS. 57(10). p.400-403
- Machine learning-based characterization of SNR in digital satellite communication links (2021) 2021 15TH EUROPEAN CONFERENCE ON ANTENNAS AND PROPAGATION (EUCAP). In Proceedings of the European Conference on Antennas and Propagation
- 2020
- Machine-learning-based hybrid random-fuzzy uncertainty quantification for EMC and SI assessment (2020) IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY. 62(6). p.2538-2546