Nicolas Knudde

Journal Article
A1
open access

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

Jixiang Qing (UGent) , Nicolas Knudde, Federico Garbuglia (UGent) , Domenico Spina (UGent) , Ivo Couckuyt (UGent) and Tom Dhaene (UGent)

(2022) ENGINEERING WITH COMPUTERS. 38(suppl. 3). p.1955-1972

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Journal Article
A1
open access

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

Federico Garbuglia (UGent) , Jixiang Qing (UGent) , Nicolas Knudde, Domenico Spina (UGent) , Ivo Couckuyt (UGent) , Dirk Deschrijver (UGent) and Tom Dhaene (UGent)

(2021) ELECTRONICS LETTERS. 57(10). p.400-403

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Conference Paper
P1
open access

Batch Bayesian active learning for feasible region identification by local penalization

Jixiang Qing (UGent) , Nicolas Knudde, Ivo Couckuyt (UGent) , Tom Dhaene (UGent) and Kohei Shintani

(2020) 2020 WINTER SIMULATION CONFERENCE (WSC). In Winter Simulation Conference Proceedings p.2779-2790

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Book Chapter
open access

Multi-objective Bayesian optimization for engineering simulation

Joachim van der Herten (UGent) , Nicolas Knudde, Ivo Couckuyt (UGent) and Tom Dhaene (UGent)

(2020) High-performance simulation-based optimization. In Studies in Computational Intelligence 833. p.47-68

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Hierarchical Gaussian process models for improved metamodeling

Nicolas Knudde, Vincent Dutordoir, Joachim van der Herten (UGent) , Ivo Couckuyt (UGent) and Tom Dhaene (UGent)

(2020) ACM TRANSACTIONS ON MODELING AND COMPUTER SIMULATION. 30(4).

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Journal Article
A1
open access

Experimental evaluation of machine learning methods for robust received signal strength-based visible light positioning

Willem Raes, Nicolas Knudde, Jorik De Bruycker, Tom Dhaene (UGent) and Nobby Stevens

(2020) SENSORS. 20(21).

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A set based design method using bayesian active learning

K. Shintani, T. Sugai, J. Ishizaki, Nicolas Knudde, Ivo Couckuyt (UGent) and Tom Dhaene (UGent)

(2020) IDETC-CIE 2020, International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, Volume 11B: 46th Design Automation Conference (DAC), Proceedings.

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PhD Thesis
open access

Gaussian processes for modelling and optimization of engineering systems

Nicolas Knudde

(2020)

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Data-efficient Gaussian process regression for accurate visible light positioning

Nicolas Knudde, Willem Raes, Jorik De Bruycker, Tom Dhaene (UGent) and Nobby Stevens

(2020) IEEE COMMUNICATIONS LETTERS. 24(8). p.1705-1709

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Journal Article
A1
open access

Indoor human activity recognition using high-dimensional sensors and deep neural networks

Baptist Vandersmissen, Nicolas Knudde, Azarakhsh Jalalvand (UGent) , Ivo Couckuyt (UGent) , Tom Dhaene (UGent) and Wesley De Neve (UGent)

(2020) NEURAL COMPUTING & APPLICATIONS. 32(16). p.12295-12309

Academic Bibliography

Nicolas Knudde

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

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

Batch Bayesian active learning for feasible region identification by local penalization

Multi-objective Bayesian optimization for engineering simulation

Hierarchical Gaussian process models for improved metamodeling

Experimental evaluation of machine learning methods for robust received signal strength-based visible light positioning

A set based design method using bayesian active learning

Gaussian processes for modelling and optimization of engineering systems

Data-efficient Gaussian process regression for accurate visible light positioning

Indoor human activity recognition using high-dimensional sensors and deep neural networks

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