4 papers
Estimating Treatment Effects in Networks under Unknown Exposure Mappings
Daan Caljon, Jente Van Belle, Wouter Verbeke
Estimating heterogeneous treatment effects in network settings is complicated by interference, meaning that the outcome of an instance can be influenced by the treatment status of…
Optimizing Treatment Allocation in the Presence of Interference
Daan Caljon, Jente Van Belle, Jeroen Berrevoets +1
In Influence Maximization (IM), the objective is to -- given a budget -- select the optimal set of entities in a network to target with a treatment so as to maximize the total effe…
Using dynamic loss weighting to boost improvements in forecast stability
Daan Caljon, Jeff Vercauteren, Simon De Vos +2
Rolling origin forecast instability refers to variability in forecasts for a specific period induced by updating the forecast when new data points become available. Recently, an ex…
Sources of Gain: Decomposing Performance in Conditional Average Dose Response Estimation
Christopher Bockel-Rickermann, Toon Vanderschueren, Tim Verdonck +1
Estimating conditional average dose responses (CADR) is an important but challenging problem. Estimators must correctly model the potentially complex relationships between covariat…