Jiang R; Singh P; Wrede F; Hellander A; Petzold L
Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods Journal Article
In: PLoS computational biology, vol. 18, no. 1, pp. e1009830, 2022.
@article{jiang2022identification,
title = {Identification of dynamic mass-action biochemical reaction networks using sparse Bayesian methods},
author = {Richard Jiang and Prashant Singh and Fredrik Wrede and Andreas Hellander and Linda Petzold},
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1009830},
doi = {https://doi.org/10.1371/journal.pcbi.1009830},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {PLoS computational biology},
volume = {18},
number = {1},
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publisher = {Public Library of Science San Francisco, CA USA},
keywords = {Bayesian Inference, Inverse Problem, Model Identification},
pubstate = {published},
tppubtype = {article}
}
Coulier A; Singh P; Sturrock M; Hellander A
Systematic comparison of modeling fidelity levels and parameter inference settings applied to negative feedback gene regulation Journal Article
In: PLOS Computational Biology, vol. 18, no. 12, pp. e1010683, 2022.
@article{coulier2022systematic,
title = {Systematic comparison of modeling fidelity levels and parameter inference settings applied to negative feedback gene regulation},
author = {Adrien Coulier and Prashant Singh and Marc Sturrock and Andreas Hellander},
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010683},
doi = {https://doi.org/10.1371/journal.pcbi.1010683},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {PLOS Computational Biology},
volume = {18},
number = {12},
pages = {e1010683},
publisher = {Public Library of Science San Francisco, CA USA},
keywords = {Bayesian Inference, Inverse Problem},
pubstate = {published},
tppubtype = {article}
}
Wrede F; Eriksson R; Jiang R; Petzold L; Engblom S; Hellander A; Singh P
Robust and integrative Bayesian neural networks for likelihood-free parameter inference Inproceedings
In: 2022 International Joint Conference on Neural Networks (IJCNN), pp. 1–10, IEEE 2022.
@inproceedings{wrede2022robust,
title = {Robust and integrative Bayesian neural networks for likelihood-free parameter inference},
author = {Fredrik Wrede and Robin Eriksson and Richard Jiang and Linda Petzold and Stefan Engblom and Andreas Hellander and Prashant Singh},
url = {https://ieeexplore.ieee.org/abstract/document/9892800
https://arxiv.org/pdf/2102.06521},
doi = {https://doi.org/10.1109/IJCNN55064.2022.9892800},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {2022 International Joint Conference on Neural Networks (IJCNN)},
pages = {1--10},
organization = {IEEE},
keywords = {Bayesian Inference, Deep Learning, Inverse Problem, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Ekmefjord M; Ait-Mlouk A; Alawadi S; Åkesson M; Singh P; Spjuth O; Toor S; Hellander A
Scalable federated machine learning with fedn Inproceedings
In: 2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pp. 555–564, IEEE 2022.
@inproceedings{ekmefjord2022scalable,
title = {Scalable federated machine learning with fedn},
author = {Morgan Ekmefjord and Addi Ait-Mlouk and Sadi Alawadi and Mattias Åkesson and Prashant Singh and Ola Spjuth and Salman Toor and Andreas Hellander},
url = {https://ieeexplore.ieee.org/abstract/document/9826069
https://arxiv.org/pdf/2103.00148
},
doi = {https://doi.org/10.1109/CCGrid54584.2022.00065},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
booktitle = {2022 22nd IEEE International Symposium on Cluster, Cloud and Internet Computing (CCGrid)},
pages = {555--564},
organization = {IEEE},
keywords = {Federated Learning, Software},
pubstate = {published},
tppubtype = {inproceedings}
}
Javed O; Singh P; Reger G; Toor S
To test, or not to test: A proactive approach for deciding complete performance test initiation Journal Article
In: arXiv preprint arXiv:2205.14749, 2022.
@article{javed2022test,
title = {To test, or not to test: A proactive approach for deciding complete performance test initiation},
author = {Omar Javed and Prashant Singh and Giles Reger and Salman Toor},
url = {https://arxiv.org/pdf/2205.14749},
year = {2022},
date = {2022-01-01},
urldate = {2022-01-01},
journal = {arXiv preprint arXiv:2205.14749},
keywords = {Software, Unsupervised Learning},
pubstate = {published},
tppubtype = {article}
}
Singh P; Wrede F; Hellander A
Scalable machine learning-assisted model exploration and inference using Sciope Journal Article
In: Bioinformatics, vol. 37, no. 2, pp. 279–281, 2021.
@article{singh2021scalable,
title = {Scalable machine learning-assisted model exploration and inference using Sciope},
author = {Prashant Singh and Fredrik Wrede and Andreas Hellander},
url = {https://academic.oup.com/bioinformatics/article/37/2/279/5876021},
doi = {https://doi.org/10.1093/bioinformatics/btaa673},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Bioinformatics},
volume = {37},
number = {2},
pages = {279--281},
publisher = {Oxford University Press},
keywords = {Bayesian Inference, Deep Learning, Inverse Problem, Optimization, Software, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Jiang R; Jacob B; Geiger M; Matthew S; Rumsey B; Singh P; Wrede F; Yi T; Drawert B; Hellander A; others
Epidemiological modeling in stochss live! Journal Article
In: Bioinformatics, vol. 37, no. 17, pp. 2787–2788, 2021.
@article{jiang2021epidemiological,
title = {Epidemiological modeling in stochss live!},
author = {Richard Jiang and Bruno Jacob and Matthew Geiger and Sean Matthew and Bryan Rumsey and Prashant Singh and Fredrik Wrede and Tau-Mu Yi and Brian Drawert and Andreas Hellander and others},
url = {https://academic.oup.com/bioinformatics/article/37/17/2787/6123781
https://academic.oup.com/bioinformatics/advance-article-pdf/doi/10.1093/bioinformatics/btab061/40342592/btab061.pdf},
doi = {https://doi.org/10.1093/bioinformatics/btab061},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {Bioinformatics},
volume = {37},
number = {17},
pages = {2787--2788},
publisher = {Oxford University Press},
keywords = {Bayesian Inference, Software},
pubstate = {published},
tppubtype = {article}
}
Akesson M; Singh P; Wrede F; Hellander A
Convolutional neural networks as summary statistics for approximate bayesian computation Journal Article
In: IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2021.
@article{akesson2021convolutional,
title = {Convolutional neural networks as summary statistics for approximate bayesian computation},
author = {Mattias Akesson and Prashant Singh and Fredrik Wrede and Andreas Hellander},
url = {https://ieeexplore.ieee.org/abstract/document/9525290},
doi = {https://doi.org/10.1109/TCBB.2021.3108695},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {IEEE/ACM Transactions on Computational Biology and Bioinformatics},
publisher = {IEEE},
keywords = {Bayesian Inference, Deep Learning, Inverse Problem},
pubstate = {published},
tppubtype = {article}
}
Jiang R M; Wrede F; Singh P; Hellander A; Petzold L R
Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators Journal Article
In: BMC bioinformatics, vol. 22, no. 1, pp. 1–17, 2021.
@article{jiang2021accelerated,
title = {Accelerated regression-based summary statistics for discrete stochastic systems via approximate simulators},
author = {Richard M Jiang and Fredrik Wrede and Prashant Singh and Andreas Hellander and Linda R Petzold},
url = {https://link.springer.com/article/10.1186/s12859-021-04255-9},
doi = {https://doi.org/10.1186/s12859-021-04255-9},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
journal = {BMC bioinformatics},
volume = {22},
number = {1},
pages = {1--17},
publisher = {BioMed Central},
keywords = {Bayesian Inference, Inverse Problem, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Ju L; Singh P; Toor S
Proactive autoscaling for edge computing systems with kubernetes Inproceedings
In: Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion, pp. 1–8, 2021.
@inproceedings{ju2021proactive,
title = {Proactive autoscaling for edge computing systems with kubernetes},
author = {Li Ju and Prashant Singh and Salman Toor},
url = {https://dl.acm.org/doi/abs/10.1145/3492323.3495588},
doi = {https://doi.org/10.1145/3492323.3495588},
year = {2021},
date = {2021-01-01},
urldate = {2021-01-01},
booktitle = {Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion},
pages = {1--8},
keywords = {Distributed Computing},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Elamin M M; Toor S
Towards Smart e-Infrastructures, A Community Driven Approach Based on Real Datasets Inproceedings
In: 2020 IEEE Green Technologies Conference (GreenTech), pp. 109–114, IEEE 2020.
@inproceedings{singh2020towards,
title = {Towards Smart e-Infrastructures, A Community Driven Approach Based on Real Datasets},
author = {Prashant Singh and Mona Mohamed Elamin and Salman Toor},
url = {https://ieeexplore.ieee.org/abstract/document/9289758
https://arxiv.org/pdf/2012.09579
},
doi = {https://doi.org/10.1109/GreenTech46478.2020.9289758},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
booktitle = {2020 IEEE Green Technologies Conference (GreenTech)},
pages = {109--114},
organization = {IEEE},
keywords = {Deep Learning, Distributed Computing, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Vats E; Hast A
Learning surrogate models of document image quality metrics for automated document image processing Inproceedings
In: 2018 13th IAPR International Workshop on Document Analysis Systems (DAS), pp. 67–72, IEEE 2018.
@inproceedings{singh2018learning,
title = {Learning surrogate models of document image quality metrics for automated document image processing},
author = {Prashant Singh and Ekta Vats and Anders Hast},
url = {https://ieeexplore.ieee.org/abstract/document/8395173
https://arxiv.org/pdf/1712.03738},
doi = {https://doi.org/10.1109/DAS.2018.14},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
booktitle = {2018 13th IAPR International Workshop on Document Analysis Systems (DAS)},
pages = {67--72},
organization = {IEEE},
keywords = {Optimization, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Hellander A
Hyperparameter optimization for approximate Bayesian computation Inproceedings
In: 2018 Winter Simulation Conference (WSC), pp. 1718–1729, IEEE 2018.
@inproceedings{singh2018hyperparameter,
title = {Hyperparameter optimization for approximate Bayesian computation},
author = {Prashant Singh and Andreas Hellander},
url = {https://ieeexplore.ieee.org/abstract/document/8632304
},
doi = {https://doi.org/10.1109/WSC.2018.8632304},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
booktitle = {2018 Winter Simulation Conference (WSC)},
pages = {1718--1729},
organization = {IEEE},
keywords = {Bayesian Inference, Inverse Problem, Optimization},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Hellander A
Multi-objective optimization driven construction of uniform priors for likelihood-free parameter inference Inproceedings
In: ESM 2018, October 24--26, Ghent, Belgium, pp. 22–27, EUROSIS 2018.
@inproceedings{singh2018multi,
title = {Multi-objective optimization driven construction of uniform priors for likelihood-free parameter inference},
author = {Prashant Singh and Andreas Hellander},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
booktitle = {ESM 2018, October 24--26, Ghent, Belgium},
pages = {22--27},
organization = {EUROSIS},
keywords = {Bayesian Inference, Inverse Problem, Optimization},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; van der Herten J; Deschrijver D; Couckuyt I; Dhaene T
A sequential sampling strategy for adaptive classification of computationally expensive data Journal Article
In: Structural and Multidisciplinary Optimization, vol. 55, no. 4, pp. 1425–1438, 2017.
@article{singh2017sequential,
title = {A sequential sampling strategy for adaptive classification of computationally expensive data},
author = {Prashant Singh and Joachim van der Herten and Dirk Deschrijver and Ivo Couckuyt and Tom Dhaene},
url = {https://link.springer.com/article/10.1007/s00158-016-1584-1
https://users.ugent.be/~didschri/papers/2017_04_Springer_SMO.pdf
},
doi = {https://doi.org/10.1007/s00158-016-1584-1},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {Structural and Multidisciplinary Optimization},
volume = {55},
number = {4},
pages = {1425--1438},
publisher = {Springer Berlin Heidelberg},
keywords = {Classification, Inverse Problem, Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Singh P; Rossi M; Couckuyt I; Deschrijver D; Rogier H; Dhaene T
Constrained multi-objective antenna design optimization using surrogates Journal Article
In: International Journal of Numerical Modelling: Electronic Networks, Devices and Fields, vol. 30, no. 6, pp. e2248, 2017.
@article{singh2017constrained,
title = {Constrained multi-objective antenna design optimization using surrogates},
author = {Prashant Singh and Marco Rossi and Ivo Couckuyt and Dirk Deschrijver and Hendrik Rogier and Tom Dhaene},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jnm.2248
http://sumo.intec.ugent.be/sites/default/files/dirk_pubs/2017_11_Wiley_IJNM.pdf},
doi = {https://doi.org/10.1002/jnm.2248},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {International Journal of Numerical Modelling: Electronic Networks, Devices and Fields},
volume = {30},
number = {6},
pages = {e2248},
keywords = {Optimization, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Singh P; Couckuyt I; Elsayed K; Deschrijver D; Dhaene T
Multi-objective geometry optimization of a gas cyclone using triple-fidelity co-kriging surrogate models Journal Article
In: Journal of Optimization Theory and Applications, vol. 175, no. 1, pp. 172–193, 2017.
@article{singh2017multi,
title = {Multi-objective geometry optimization of a gas cyclone using triple-fidelity co-kriging surrogate models},
author = {Prashant Singh and Ivo Couckuyt and Khairy Elsayed and Dirk Deschrijver and Tom Dhaene},
url = {https://link.springer.com/article/10.1007/s10957-017-1114-3
http://sumo.intec.ugent.be/sites/default/files/dirk_pubs/2017_10_Springer_JOTA.pdf},
doi = {https://doi.org/10.1007/s10957-017-1114-3},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {Journal of Optimization Theory and Applications},
volume = {175},
number = {1},
pages = {172--193},
publisher = {Springer US},
keywords = {Optimization, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Singh P; Hellander A
Surrogate assisted model reduction for stochastic biochemical reaction networks Inproceedings
In: 2017 Winter Simulation Conference (WSC), pp. 1773–1783, IEEE 2017.
@inproceedings{singh2017surrogate,
title = {Surrogate assisted model reduction for stochastic biochemical reaction networks},
author = {Prashant Singh and Andreas Hellander},
url = {https://ieeexplore.ieee.org/abstract/document/8247915
},
doi = {https://doi.org/10.1109/WSC.2017.8247915},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
booktitle = {2017 Winter Simulation Conference (WSC)},
pages = {1773--1783},
organization = {IEEE},
keywords = {Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Vats E; Hast A; Singh P
Automatic document image binarization using bayesian optimization Inproceedings
In: Proceedings of the 4th International Workshop on Historical Document Imaging and Processing, pp. 89–94, 2017.
@inproceedings{vats2017automatic,
title = {Automatic document image binarization using bayesian optimization},
author = {Ekta Vats and Anders Hast and Prashant Singh},
url = {https://dl.acm.org/doi/abs/10.1145/3151509.3151520
https://arxiv.org/pdf/1709.01782
},
doi = {https://doi.org/10.1145/3151509.3151520},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
booktitle = {Proceedings of the 4th International Workshop on Historical Document Imaging and Processing},
pages = {89--94},
keywords = {Optimization, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Couckuyt I; Elsayed K; Deschrijver D; Dhaene T
Shape optimization of a cyclone separator using multi-objective surrogate-based optimization Journal Article
In: Applied Mathematical Modelling, vol. 40, no. 5-6, pp. 4248–4259, 2016.
@article{singh2016shape,
title = {Shape optimization of a cyclone separator using multi-objective surrogate-based optimization},
author = {Prashant Singh and Ivo Couckuyt and Khairy Elsayed and Dirk Deschrijver and Tom Dhaene},
url = {https://www.sciencedirect.com/science/article/pii/S0307904X15007210
http://sumo.intec.ugent.be/sites/default/files/dirk_pubs/2016_03_Elsevier_APM.pdf},
doi = {https://doi.org/10.1016/j.apm.2015.11.007},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
journal = {Applied Mathematical Modelling},
volume = {40},
number = {5-6},
pages = {4248--4259},
publisher = {Elsevier},
keywords = {Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Singh P
Design of experiments for model-based optimization PhD Thesis
Ghent University, 2016.
@phdthesis{singh2016design,
title = {Design of experiments for model-based optimization},
author = {Prashant Singh},
url = {https://biblio.ugent.be/publication/7223691/file/7223692},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
school = {Ghent University},
keywords = {Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {phdthesis}
}
Singh P; Claeys T; Vandenbosch G A; Pissoort D
Automated line-based sequential sampling and modeling algorithm for EMC near-field scanning Journal Article
In: IEEE Transactions on Electromagnetic Compatibility, vol. 59, no. 2, pp. 704–709, 2016.
@article{singh2016automated,
title = {Automated line-based sequential sampling and modeling algorithm for EMC near-field scanning},
author = {Prashant Singh and Tim Claeys and Guy AE Vandenbosch and Davy Pissoort},
url = {https://ieeexplore.ieee.org/abstract/document/7776759
https://lirias.kuleuven.be/retrieve/639699},
doi = {https://doi.org/10.1109/TEMC.2016.2632741},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
journal = {IEEE Transactions on Electromagnetic Compatibility},
volume = {59},
number = {2},
pages = {704--709},
publisher = {IEEE},
keywords = {Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Gong X; Trogh J; Braet Q; Tanghe E; Singh P; Plets D; Hoebeke J; Deschrijver D; Dhaene T; Martens L; others
Measurement-based wireless network planning, monitoring, and reconfiguration solution for robust radio communications in indoor factories Journal Article
In: IET Science, Measurement & Technology, vol. 10, no. 4, pp. 375–382, 2016.
@article{gong2016measurement,
title = {Measurement-based wireless network planning, monitoring, and reconfiguration solution for robust radio communications in indoor factories},
author = {Xu Gong and Jens Trogh and Quentin Braet and Emmeric Tanghe and Prashant Singh and David Plets and Jeroen Hoebeke and Dirk Deschrijver and Tom Dhaene and Luc Martens and others},
url = {https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/iet-smt.2015.0213
https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-smt.2015.0213},
doi = {https://doi.org/10.1049/iet-smt.2015.0213},
year = {2016},
date = {2016-01-01},
urldate = {2016-01-01},
journal = {IET Science, Measurement & Technology},
volume = {10},
number = {4},
pages = {375--382},
publisher = {The Institution of Engineering and Technology},
keywords = {Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Vermeeren G; Singh P; Aerts S; Deschrijver D; Dhaene T; Joseph W; Martens L
Surrogate-based fast peak mass-averaged SAR assessment Inproceedings
In: Annual Meeting of the Bioelectromagnetics Society and the European BioElectromagnetics Association (BioEM 2015), pp. 135–137, 2015.
@inproceedings{vermeeren2015surrogate,
title = {Surrogate-based fast peak mass-averaged SAR assessment},
author = {Günter Vermeeren and Prashant Singh and Sam Aerts and Dirk Deschrijver and Tom Dhaene and Wout Joseph and Luc Martens},
url = {https://biblio.ugent.be/publication/7257304/file/7257373.pdf},
year = {2015},
date = {2015-01-01},
urldate = {2015-01-01},
booktitle = {Annual Meeting of the Bioelectromagnetics Society and the European BioElectromagnetics Association (BioEM 2015)},
pages = {135--137},
keywords = {Inverse Problem, Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Couckuyt I; Ferranti F; Dhaene T
A constrained multi-objective surrogate-based optimization algorithm Inproceedings
In: 2014 IEEE Congress on Evolutionary Computation (CEC), pp. 3080–3087, IEEE 2014.
@inproceedings{singh2014constrained,
title = {A constrained multi-objective surrogate-based optimization algorithm},
author = {Prashant Singh and Ivo Couckuyt and Francesco Ferranti and Tom Dhaene},
url = {https://ieeexplore.ieee.org/abstract/document/6900581
https://biblio.ugent.be/publication/5733039/file/5733050.pdf},
doi = {https://doi.org/10.1109/CEC.2014.6900581},
year = {2014},
date = {2014-01-01},
urldate = {2014-01-01},
booktitle = {2014 IEEE Congress on Evolutionary Computation (CEC)},
pages = {3080--3087},
organization = {IEEE},
keywords = {Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Ferranti F; Deschrijver D; Couckuyt I; Dhaene T
Classification aided domain reduction for high dimensional optimization Inproceedings
In: Proceedings of the Winter Simulation Conference 2014, pp. 3928–3939, IEEE 2014.
@inproceedings{singh2014classification,
title = {Classification aided domain reduction for high dimensional optimization},
author = {Prashant Singh and Francesco Ferranti and Dirk Deschrijver and Ivo Couckuyt and Tom Dhaene},
url = {https://ieeexplore.ieee.org/abstract/document/7020218
https://biblio.ugent.be/publication/5955500/file/5955522},
doi = {https://doi.org/10.1109/WSC.2014.7020218},
year = {2014},
date = {2014-01-01},
urldate = {2014-01-01},
booktitle = {Proceedings of the Winter Simulation Conference 2014},
pages = {3928--3939},
organization = {IEEE},
keywords = {Classification, Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Deschrijver D; Pissoort D; Dhaene T
Adaptive classification algorithm for EMC-compliance testing of electronic devices Journal Article
In: Electronics Letters, vol. 49, no. 24, pp. 1526–1528, 2013.
@article{singh2013adaptive,
title = {Adaptive classification algorithm for EMC-compliance testing of electronic devices},
author = {Prashant Singh and Dirk Deschrijver and Davy Pissoort and Tom Dhaene},
url = {https://ietresearch.onlinelibrary.wiley.com/doi/full/10.1049/el.2013.2766
https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/el.2013.2766},
doi = {https://doi.org/10.1049/el.2013.2766},
year = {2013},
date = {2013-01-01},
urldate = {2013-01-01},
journal = {Electronics Letters},
volume = {49},
number = {24},
pages = {1526--1528},
publisher = {The Institution of Engineering and Technology},
keywords = {Classification, Inverse Problem, Optimization, Surrogate Modeling},
pubstate = {published},
tppubtype = {article}
}
Singh P; Deschrijver D; Dhaene T
A balanced sequential design strategy for global surrogate modeling Inproceedings
In: 2013 Winter Simulations Conference (WSC), pp. 2172–2179, IEEE 2013.
@inproceedings{singh2013balanced,
title = {A balanced sequential design strategy for global surrogate modeling},
author = {Prashant Singh and Dirk Deschrijver and Tom Dhaene},
url = {https://ieeexplore.ieee.org/abstract/document/6721594
https://biblio.ugent.be/publication/4315532/file/4315539},
doi = {https://doi.org/10.1109/WSC.2013.6721594},
year = {2013},
date = {2013-01-01},
urldate = {2013-01-01},
booktitle = {2013 Winter Simulations Conference (WSC)},
pages = {2172--2179},
organization = {IEEE},
keywords = {Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}
Singh P; Deschrijver D; Pissoort D; Dhaene T
Accurate hotspot localization by sampling the near-field pattern of electronic devices Journal Article
In: IEEE Transactions on Electromagnetic Compatibility, vol. 55, no. 6, pp. 1365–1368, 2013.
@article{singh2013accurate,
title = {Accurate hotspot localization by sampling the near-field pattern of electronic devices},
author = {Prashant Singh and Dirk Deschrijver and Davy Pissoort and Tom Dhaene},
url = {https://ieeexplore.ieee.org/abstract/document/6522868
https://biblio.ugent.be/publication/4210867/file/4210870.pdf},
doi = {https://doi.org/10.1109/TEMC.2013.2265158},
year = {2013},
date = {2013-01-01},
urldate = {2013-01-01},
journal = {IEEE Transactions on Electromagnetic Compatibility},
volume = {55},
number = {6},
pages = {1365--1368},
publisher = {IEEE},
keywords = {Inverse Problem, Optimization, Sampling},
pubstate = {published},
tppubtype = {article}
}
Singh P; Deschrijver D; Pissoort D; Dhaene T
Efficient measurement procedure for hotspot detection in near-field pattern of electronic devices Inproceedings
In: BESTCOM Meeting, 2013.
@inproceedings{singh2013efficient,
title = {Efficient measurement procedure for hotspot detection in near-field pattern of electronic devices},
author = {Prashant Singh and Dirk Deschrijver and Davy Pissoort and Tom Dhaene},
url = {https://biblio.ugent.be/publication/4083180/file/4083328.pdf},
year = {2013},
date = {2013-01-01},
urldate = {2013-01-01},
booktitle = {BESTCOM Meeting},
keywords = {Inverse Problem, Optimization, Sampling, Surrogate Modeling},
pubstate = {published},
tppubtype = {inproceedings}
}