Ghent University Academic Bibliography

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tsdownsample : high-performance time series downsampling for scalable visualization

Jeroen Van Der Donckt (UGent) , Jonas Van Der Donckt (UGent) and Sofie Van Hoecke (UGent)

(2025) SOFTWAREX. 29.
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- P1
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Data quality strategies in gas metal arc welding production for machine learning applications

Jorge Iván Rodríguez Echeverría (UGent) , Evans Doe Ocansey, Roxana-Maria Holom, Tomasz Piotr Michno, Hannes Hinterbichler, Pauline Meyer-Heye and Sidharta Gautama (UGent)

(2025) DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, SPECIAL SESSIONS I, 21ST INTERNATIONAL CONFERENCE. In Lecture Notes in Networks and Systems 1198. p.83-94
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ReSurveyEurope : a database of resurveyed vegetation plots in Europe

Ilona Knollova, Milan Chytry, Helge Bruelheide, Stefan Dullinger, Ute Jandt, Markus Bernhardt-Romermann, Idoia Biurrun, Francesco de Bello, Michael Glaser, Stephan Hennekens, et al.

(2024) JOURNAL OF VEGETATION SCIENCE. 35(2).
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Melanin-based color variation in response to changing climates in snakes

Jonathan Goldenberg (UGent) , Karen Bisschop (UGent) , G. Bruni, Matteo Riccardo Di Nicola (UGent) , F. Banfi and F. P. Faraone

(2024) ECOLOGY AND EVOLUTION. 14(7).
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Goats on the move : evaluating machine learning models for goat activity analysis using accelerometer data

Arthur Hollevoet, Timo De Waele (UGent) , Daniel Peralta (UGent) , Frank Tuyttens (UGent) , Eli De Poorter (UGent) and Adnan Shahid (UGent)

(2024) ANIMALS. 14(13).
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Gradients of O-information highlight synergy and redundancy in physiological applications

Tomas Scagliarini, Laura Sparacino, Luca Faes, Daniele Marinazzo (UGent) and Sebastiano Stramaglia

(2024) FRONTIERS IN NETWORK PHYSIOLOGY. 3.
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Robust interactive fixed effects

Kris Boudt (UGent) and Ewoud Heyndels

(2024) ECONOMETRICS AND STATISTICS. 29. p.206-223
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MinMaxLTTB : leveraging MinMax-preselection to scale LTTB

Jeroen Van Der Donckt (UGent) , Jonas Van Der Donckt (UGent) , Michaël Rademaker (UGent) and Sofie Van Hoecke (UGent)

(2023) 2023 IEEE Visualization and Visual Analytics (VIS). In IEEE Visualization Conference p.21-25
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Do not sleep on traditional machine learning simple and interpretable techniques are competitive to deep learning for sleep scoring

Jeroen Van Der Donckt (UGent) , Jonas Van Der Donckt (UGent) , Emiel Deprost (UGent) , Nicolas Vandenbussche (UGent) , Michael Rademaker, Gilles Vandewiele (UGent) and Sofie Van Hoecke (UGent)

(2023) BIOMEDICAL SIGNAL PROCESSING AND CONTROL. 81.
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- C3
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A comparative study of event detection methods in fusion devices with an application to edge-localized modes

Jerome Alhage (UGent) , Casper Haems (UGent) , Mateo Van Damme, Geert Verdoolaege (UGent) and (EUROfusion) JET CONTRIBUTORS*

(2023) 5th IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis, Abstracts.

Academic Bibliography

tsdownsample : high-performance time series downsampling for scalable visualization

Data quality strategies in gas metal arc welding production for machine learning applications

ReSurveyEurope : a database of resurveyed vegetation plots in Europe

Melanin-based color variation in response to changing climates in snakes

Goats on the move : evaluating machine learning models for goat activity analysis using accelerometer data

Gradients of O-information highlight synergy and redundancy in physiological applications

Robust interactive fixed effects

MinMaxLTTB : leveraging MinMax-preselection to scale LTTB

Do not sleep on traditional machine learning simple and interpretable techniques are competitive to deep learning for sleep scoring

A comparative study of event detection methods in fusion devices with an application to edge-localized modes

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