Katrien Antonio

17 papers B 1Journal 16
YearRankTypeTitle / Venue / Authors
2025 J jnl
A multi-view contrastive learning framework for spatial embeddings in risk modelling.
CoRR
Freek Holvoet, Christopher Blier-Wong, Katrien Antonio
2025 J jnl
Machine Learning with Multitype Protected Attributes: Intersectional Fairness through Regularisation.
CoRR
Ho Ming Lee, Katrien Antonio, Benjamin Avanzi, Lorenzo Marchi, Rui Zhou
2025 J jnl
Machine learning in an expectation-maximisation framework for nowcasting.
CoRR
Paul Wilsens, Katrien Antonio, Gerda Claeskens
2025 J jnl
Reducing the dimensionality and granularity in hierarchical categorical variables.
Adv. Data Anal. Classif.
Paul Wilsens, Katrien Antonio, Gerda Claeskens
2025 J jnl
The use of IoT sensor data to dynamically assess maintenance risk in service contracts.
Eur. J. Oper. Res.
Stijn Loeys, Robert N. Boute, Katrien Antonio
2023 J jnl
An engine to simulate insurance fraud network data.
CoRR
Bavo D. C. Campo, Katrien Antonio
2023 J jnl
Data-driven preventive maintenance for a heterogeneous machine portfolio.
Oper. Res. Lett.
Laurens Deprez, Katrien Antonio, Joachim J. Arts, Robert N. Boute
2023 J jnl
Empirical risk assessment of maintenance costs under full-service contracts.
Eur. J. Oper. Res.
Laurens Deprez, Katrien Antonio, Robert N. Boute
2023 J jnl
Neural networks for insurance pricing with frequency and severity data: a benchmark study from data preprocessing to technical tariff.
CoRR
Freek Holvoet, Katrien Antonio, Roel Henckaerts
2022 J jnl
When stakes are high: Balancing accuracy and transparency with Model-Agnostic Interpretable Data-driven suRRogates.
Expert Syst. Appl.
Roel Henckaerts, Katrien Antonio, Marie-Pier Côté
2021 J jnl
Pricing service maintenance contracts using predictive analytics.
Eur. J. Oper. Res.
Laurens Deprez, Katrien Antonio, Robert N. Boute
2020 J jnl
Model-Agnostic Interpretable and Data-driven suRRogates suited for highly regulated industries.
CoRR
Roel Henckaerts, Katrien Antonio, Marie-Pier Côté
2020 J jnl
Social network analytics for supervised fraud detection in insurance.
CoRR
María Óskarsdóttir, Waqas Ahmed, Katrien Antonio, Bart Baesens, Rémi Dendievel, Tom Donas, Tom Reynkens
2019 J jnl
Boosting insights in insurance tariff plans with tree-based machine learning.
CoRR
Roel Henckaerts, Marie-Pier Côté, Katrien Antonio, Roel Verbelen
2019 J jnl
Modeling the number of hidden events subject to observation delay.
Eur. J. Oper. Res.
Jonas Crevecoeur, Katrien Antonio, Roel Verbelen
2018 J jnl
Profit maximizing logistic model for customer churn prediction using genetic algorithms.
Swarm Evol. Comput.
Eugen Stripling, Seppe vanden Broucke, Katrien Antonio, Bart Baesens, Monique Snoeck
2015 B conf
Profit maximizing logistic regression modeling for customer churn prediction.
DSAA
Eugen Stripling, Seppe vanden Broucke, Katrien Antonio, Bart Baesens, Monique Snoeck