ProductNetworks TractableProbabilisticModels

However,as already suggested, our model is not restricted to any specific intervention type or instantiation. Figure 1 (a) illustrates the performance of iSPN on theCausal Health data setfordifferent intervention types (perfect, atomic), noise terms (Gaussian, Gamma, Beta) and instantiations (Indicator Functions, Modifications). Nonetheless, it can be observed that some interventions are being modelled more precisely than others, e.g. ForEarthquakeand Cancer data sets, we use 5 different number ofsum node weights: 600, 1200, 1800, 2400 and3200. Forthesynthetic causal health data set we use 300, 600, 1000, 1500, 2000.