Ghent University Academic Bibliography

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A collaboration between judge and machine to reduce legal uncertainty in disputes concerning ex aequo et bono compensations

Wim De Mulder (UGent) , Peggy Valcke and Joke Baeck (UGent)

(2022) ARTIFICIAL INTELLIGENCE AND LAW.
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Paradoxical tensions related to AI-powered evaluation systems in competitive sports

Elena Mazurova, Willem Standaert (UGent) , Esko Penttinen and Felix Ter Chian Tan

(2022) INFORMATION SYSTEMS FRONTIERS. 24(3). p.897-922
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- Journal Article
- A1
- open access
Challenges in translational machine learning

Artuur Couckuyt (UGent) , Ruth Seurinck (UGent) , Annelies Emmaneel (UGent) , Katrien Quintelier (UGent) , David Novák (UGent) , Sofie Van Gassen (UGent) and Yvan Saeys (UGent)

(2022) HUMAN GENETICS. 141. p.1451-1466
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- Journal Article
- A1
- open access
Machine learning based interpretation of microkinetic data : a Fischer-Tropsch synthesis case study

Anoop Chakkingal (UGent) , Pieter Janssens (UGent) , Jeroen Poissonnier (UGent) , Alan Josue Barrios Medina (UGent) , Mirella Virginie, Andrei Khodakov and Joris Thybaut (UGent)

(2021) REACTION CHEMISTRY & ENGINEERING. 7(1). p.101-110
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- Journal Article
- A1
- open access
Machine learning in chemical engineering : strengths, weaknesses, opportunities, and threats

Maarten Dobbelaere (UGent) , Pieter Plehiers, Ruben Van de Vijver (UGent) , Christian Stevens (UGent) and Kevin Van Geem (UGent)

(2021) ENGINEERING. 7(9). p.1201-1211

Academic Bibliography

A collaboration between judge and machine to reduce legal uncertainty in disputes concerning ex aequo et bono compensations

Paradoxical tensions related to AI-powered evaluation systems in competitive sports

Challenges in translational machine learning

Machine learning based interpretation of microkinetic data : a Fischer-Tropsch synthesis case study

Machine learning in chemical engineering : strengths, weaknesses, opportunities, and threats

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