Runtime Prediction Based Grid Scheduling of Parameter Sweep Jobs. - Sam Verboven; Peter Hellinckx; Frans Arickx; Jan Broeckhove (APSCC, 2008)

Dynamic Grid Scheduling Using Job Runtime Requirements and Variable Resource Availability. - Sam Verboven; Peter Hellinckx; Jan Broeckhove; Frans Arickx (Euro-Par, 2008)

Predicting Parameter Sweep Jobs: From Simulation to Grid Implementation. - Peter Hellinckx; Sam Verboven; Frans Arickx; Jan Broeckhove (CISIS, 2009)

Runtime Prediction in Desktop Grid Scheduling. - Peter Hellinckx; Sam Verboven; Frans Arickx; Jan Broeckhove (Parallel Programming, Models and Applications in Grid and P2P Systems, 2009)

Multiplexing Low and High QoS Workloads in Virtual Environments. - Sam Verboven; Kurt Vanmechelen; Jan Broeckhove (JSSPP, 2010)

Black box scheduling for resource intensive virtual machine workloads with interference models. - Sam Verboven; Kurt Vanmechelen; Jan Broeckhove (Future Gener. Comput. Syst., 2013)

Model driven scheduling for virtualized workloads - Sam Verboven (2013)

Network Aware Scheduling for Virtual Machine Workloads with Interference Models. - Sam Verboven; Kurt Vanmechelen; Jan Broeckhove (IEEE Trans. Serv. Comput., 2015)

Optimising Individual-Treatment-Effect Using Bandits. - Jeroen Berrevoets; Sam Verboven; Wouter Verbeke (CoRR, 2019)

HydaLearn: Highly Dynamic Task Weighting for Multi-task Learning with Auxiliary Tasks. - Sam Verboven; Muhammad Hafeez Chaudhary; Jeroen Berrevoets; Wouter Verbeke (CoRR, 2020)

Combining the Clinical and Operational Perspectives in Heterogeneous Treatment Effect Inference in Healthcare Processes. - Sam Verboven; Niels Martin (ICPM Workshops, 2021)

Autoencoders for strategic decision support. - Sam Verboven; Jeroen Berrevoets; Chris Wuytens; Bart Baesens; Wouter Verbeke (Decis. Support Syst., 2021)

Mining Statistical Relations for Better Decision Making in Healthcare Processes. - Jelmer Jan Koorn; Xixi Lu 001; Henrik Leopold; Niels Martin; Sam Verboven; Hajo A. Reijers (ICPM, 2022)

Towards Sustainable Power Systems: Exploring the Opportunities of Multi-task Learning for Battery Degradation Forecasting. - Emilie Grégoire; Sam Verboven (AI4KMES@ECAI, 2023)

A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions. - Christopher Bockel-Rickermann; Sam Verboven; Tim Verdonck; Wouter Verbeke (CoRR, 2023)

HydaLearn. - Sam Verboven; Muhammad Hafeez Chaudhary; Jeroen Berrevoets; Vincent Ginis; Wouter Verbeke (Appl. Intell., 2023)

DynamITE: Optimal time-sensitive organ offers using ITE. - Alessandro Marchese; Hans de Ferrante; Jeroen Berrevoets; Sam Verboven (ML4H@NeurIPS, 2024)

Sample-level weighting for multi-task learning with auxiliary tasks. - Emilie Grégoire; Muhammad Hafeez Chaudhary; Sam Verboven (Appl. Intell., 2024)

Hybrid black-box classification for customer churn prediction with segmented interpretability analysis. - Arno De Caigny; Koen W. De Bock; Sam Verboven (Decis. Support Syst., 2024)

Can causal machine learning reveal individual bid responses of bank customers? - A study on mortgage loan applications in Belgium. - Christopher Bockel-Rickermann; Sam Verboven; Tim Verdonck; Wouter Verbeke (Decis. Support Syst., 2025)

Flexible Counterfactual Explanations with Generative Models. - Stig Hellemans; Andres Algaba; Sam Verboven; Vincent Ginis (CoRR, 2025)

Engineering the Law-Machine Learning Translation Problem: Developing Legally Aligned Models. - Mathias Hanson; Gregory Lewkowicz; Sam Verboven (CoRR, 2025)

Decision-centric fairness: Evaluation and optimization for resource allocation problems. - Simon De Vos; Jente Van Belle; Andres Algaba; Wouter Verbeke; Sam Verboven (CoRR, 2025)