dr. Heidelinde Dehaene

Journal Article
A1
open access

Why synthetic discoveries are not only a problem of differentially private synthetic data

Heidelinde Dehaene (UGent) , Alexander Decruyenaere (UGent) , Christiaan Polet (UGent) , Johan Decruyenaere (UGent) , Paloma Rabaey (UGent) , Thomas Demeester (UGent) and Stijn Vansteelandt (UGent)

(2024) METHODS OF INFORMATION IN MEDICINE. 63(05/06). p.203-204

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Inference failure with synthetic arms : empirical application to phase III oncology trials

Alexander Decruyenaere (UGent) , Heidelinde Dehaene (UGent) , Paloma Rabaey (UGent) , Charles Polet (UGent) , Johan Decruyenaere (UGent) , Toon Demeester (UGent) , Stijn Vansteelandt (UGent) and Sylvie Rottey (UGent)

(2024) ANNALS OF ONCOLOGY. In Annals of Oncology 35(Supplement 2). p.S526-S527

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Conference Paper
C1
open access

Debiasing synthetic data generated by deep generative models

Alexander Decruyenaere (UGent) , Heidelinde Dehaene (UGent) , Paloma Rabaey (UGent) , Johan Decruyenaere (UGent) , Christiaan Polet (UGent) , Thomas Demeester (UGent) and Stijn Vansteelandt (UGent)

(2024) Advances in Neural Information Processing Systems 37 (NeurIPS 2024). In Advances in Neural Information Processing Systems 37.

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Conference Paper
P1
open access

The real deal behind the artificial appeal : inferential utility of tabular synthetic data

Alexander Decruyenaere (UGent) , Heidelinde Dehaene (UGent) , Paloma Rabaey (UGent) , Christiaan Polet (UGent) , Johan Decruyenaere (UGent) , Stijn Vansteelandt (UGent) and Thomas Demeester (UGent)

(2024) UNCERTAINTY IN ARTIFICIAL INTELLIGENCE. In Proceedings of Machine Learning Research (PMLR) 244. p.966-996

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Conference Paper
C1
open access

Synthetic data : can we trust statistical estimators?

Alexander Decruyenaere (UGent) , Heidelinde Dehaene (UGent) , Paloma Rabaey (UGent) , Christiaan Polet (UGent) , Johan Decruyenaere (UGent) , Stijn Vansteelandt (UGent) and Thomas Demeester (UGent)

(2023) 1st Workshop on Deep Generative Models for Health at NeurIPS 2023, Proceedings.

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Journal Article
A1
open access

Exploring the effectiveness of clinical simulations to develop student teachers’ parent-teacher communication competence

Karen De Coninck, Karolien Keppens (UGent) , Martin Valcke (UGent) , Heidelinde Dehaene (UGent) , Jan De Neve (UGent) and Ruben Vanderlinde (UGent)

(2023) RESEARCH PAPERS IN EDUCATION. 38(1). p.69-101

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PhD Thesis

Analyzing latent outcomes via ranks

Heidelinde Dehaene (UGent)

(2022)

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Journal Article
A1
open access

A Wilcoxon–Mann–Whitney test for latent variables

Heidelinde Dehaene (UGent) , Jan De Neve (UGent) and Yves Rosseel (UGent)

(2021) FRONTIERS IN PSYCHOLOGY. 12.

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Semiparametric linear transformation models for indirectly observed outcomes

Jan De Neve (UGent) and Heidelinde Dehaene (UGent)

(2021) STATISTICS IN MEDICINE. 40(9). p.2286-2303

Academic Bibliography

dr. Heidelinde Dehaene

Why synthetic discoveries are not only a problem of differentially private synthetic data

Inference failure with synthetic arms : empirical application to phase III oncology trials

Debiasing synthetic data generated by deep generative models

The real deal behind the artificial appeal : inferential utility of tabular synthetic data

Synthetic data : can we trust statistical estimators?

Exploring the effectiveness of clinical simulations to develop student teachers’ parent-teacher communication competence

Analyzing latent outcomes via ranks

A Wilcoxon–Mann–Whitney test for latent variables

Semiparametric linear transformation models for indirectly observed outcomes

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