Predicting Day-Ahead Stock Returns using Search Engine Query Volumes: An Application of Gradient Boosted Decision Trees to the S&P 100. - Christopher Bockel-Rickermann (CoRR, 2022)

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)

Learning continuous-valued treatment effects through representation balancing. - Christopher Bockel-Rickermann; Toon Vanderschueren; Jeroen Berrevoets; Tim Verdonck; Wouter Verbeke (CoRR, 2023)

Fraud analytics: A decade of research: Organizing challenges and solutions in the field. - Christopher Bockel-Rickermann; Tim Verdonck; Wouter Verbeke (Expert Syst. Appl., 2023)

Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation. - Christopher Bockel-Rickermann; Toon Vanderschueren; Tim Verdonck; Wouter Verbeke (CoRR, 2024)

Uplift modeling with continuous treatments: A predict-then-optimize approach. - Simon De Vos; Christopher Bockel-Rickermann; Stefan Lessmann; Wouter Verbeke (CoRR, 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)

Using representation balancing to learn conditional-average dose responses from clustered data. - Christopher Bockel-Rickermann; Toon Vanderschueren; Jeroen Berrevoets; Tim Verdonck; Wouter Verbeke (Trans. Mach. Learn. Res., 2025)