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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.

Links | BibTeX | Tags: Bayesian Inference, Inverse Problem, Model Identification

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.

Links | BibTeX | Tags: Bayesian Inference, Inverse Problem

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.

Links | BibTeX | Tags: Bayesian Inference, Deep Learning, Inverse Problem, Surrogate Modeling

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.

Links | BibTeX | Tags: Federated Learning, Software

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.

Links | BibTeX | Tags: Software, Unsupervised Learning

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.

Links | BibTeX | Tags: Bayesian Inference, Deep Learning, Inverse Problem, Optimization, Software, Surrogate Modeling

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.

Links | BibTeX | Tags: Bayesian Inference, Software

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.

Links | BibTeX | Tags: Bayesian Inference, Deep Learning, Inverse Problem

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.

Links | BibTeX | Tags: Bayesian Inference, Inverse Problem, Surrogate Modeling

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.

Links | BibTeX | Tags: Distributed Computing

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.

Links | BibTeX | Tags: Deep Learning, Distributed Computing, Surrogate Modeling

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.

Links | BibTeX | Tags: Optimization, Surrogate Modeling

Singh P; Hellander A

Hyperparameter optimization for approximate Bayesian computation Inproceedings

In: 2018 Winter Simulation Conference (WSC), pp. 1718–1729, IEEE 2018.

Links | BibTeX | Tags: Bayesian Inference, Inverse Problem, Optimization

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.

BibTeX | Tags: Bayesian Inference, Inverse Problem, Optimization

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.

Links | BibTeX | Tags: Classification, Inverse Problem, Optimization, Sampling, Surrogate Modeling

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.

Links | BibTeX | Tags: Optimization, Surrogate Modeling

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.

Links | BibTeX | Tags: Optimization, Surrogate Modeling

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.

Links | BibTeX | Tags: Surrogate Modeling

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.

Links | BibTeX | Tags: Optimization, Surrogate Modeling

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.

Links | BibTeX | Tags: Optimization, Sampling, Surrogate Modeling

Singh P

Design of experiments for model-based optimization PhD Thesis

Ghent University, 2016.

Links | BibTeX | Tags: Optimization, Sampling, Surrogate Modeling

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.

Links | BibTeX | Tags: Optimization, Sampling, Surrogate Modeling

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.

Links | BibTeX | Tags: Optimization, Sampling, Surrogate Modeling

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.

Links | BibTeX | Tags: Inverse Problem, Optimization, Sampling, Surrogate Modeling

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.

Links | BibTeX | Tags: Optimization, Sampling, Surrogate Modeling

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.

Links | BibTeX | Tags: Classification, Optimization, Sampling, Surrogate Modeling

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.

Links | BibTeX | Tags: Classification, Inverse Problem, Optimization, Surrogate Modeling

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.

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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.

Links | BibTeX | Tags: Inverse Problem, Optimization, Sampling

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.

Links | BibTeX | Tags: Inverse Problem, Optimization, Sampling, Surrogate Modeling