Research Explorer

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Researcher

Federico Garbuglia

Awards & Distinctions

14 Results

2024

Evaluation of machine learning models for received signal strength based visible light positioning with obstacles

Jorik De BruyckerMichiel De WildeFederico GarbugliaIoana NikovaIvo CouckuytTom DhaeneNobby Stevens

2023

Bayesian active learning for modeling and optimization of microwave devices

Federico GarbugliaTom DhaeneDirk Deschrijver

Bayesian optimization for microwave devices using deep GP spectral surrogate models

Federico GarbugliaDomenico SpinaDirk DeschrijverIvo CouckuytTom Dhaene

A1 Journal Article in IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES

Bi-objective Bayesian optimization of engineering problems with cheap and expensive cost functions

Nasrulloh Ratu Bagus Satrio LokaIvo CouckuytFederico GarbugliaDomenico SpinaInneke Van NieuwenhuyseTom Dhaene

A1 Journal Article in ENGINEERING WITH COMPUTERS

Modeling S-parameters of interconnects using periodic Gaussian process kernels

Federico GarbugliaDomenico SpinaTorsten ReuschelChristian SchusterDirk DeschrijverTom Dhaene

Modeling electrically long interconnects using physics-informed delayed gaussian processes

Federico GarbugliaTorsten ReuschelChristian SchusterDirk DeschrijverTom DhaeneDomenico Spina

A1 Journal Article in IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY

On the role of Bayesian learning for electronic design automation : a survey

Federico GarbugliaDirk DeschrijverTom Dhaene

A2 Journal Article in IEEE ELECTROMAGNETIC COMPATIBILITY MAGAZINE

2022

Adaptive sampling with automatic stopping for feasible region identification in engineering design

Jixiang QingNicolas KnuddeFederico GarbugliaDomenico SpinaIvo CouckuytTom Dhaene

A1 Journal Article in ENGINEERING WITH COMPUTERS

Bayesian active learning for radiation pattern sampling over cylindrical surfaces

Federico GarbugliaTim ClaeysIvo CouckuytDirk DeschrijverTom Dhaene

A1 Journal Article in IEEE TRANSACTIONS ON ELECTROMAGNETIC COMPATIBILITY

Bayesian active learning for received signal strength-based visible light positioning

Federico GarbugliaWillem RaesJorik De BruyckerNobby StevensDirk DeschrijverTom Dhaene

A1 Journal Article in IEEE PHOTONICS JOURNAL

Deep learning techniques for digital satellite communications

Federico GarbugliaTom DhaeneDomenico Spina

Bookchapter in Applications of deep learning in electromagnetics : teaching Maxwell's equations to machines

S-parameter modeling and optimization using deep Gaussian processes

Federico GarbugliaDomenico SpinaDirk DeschrijverIvo CouckuytTom Dhaene

2021

Bayesian active learning for multi-objective feasible region identification in microwave devices

Federico GarbugliaJixiang QingNicolas KnuddeDomenico SpinaIvo CouckuytDirk DeschrijverTom Dhaene

A1 Journal Article in ELECTRONICS LETTERS

2020

Evaluation of generative modeling techniques for frequency responses

Federico GarbugliaDomenico SpinaDirk DeschrijverTom Dhaene