Publications

Representing, learning, and reasoning about knowledge are central to artificial intelligence (AI). A long standing goal of AI is unifying logic and probability, to benefit from the strengths of both formalisms. Probability theory allows us to represent and reason in uncertain domains, while first-order logic allows us to represent and reason about structured, relational domains. Many real-world problems exhibit both uncertainty and structure, ...

Statistical relational models combine aspects of first-order logic and probabilistic graphical models, enabling them to model complex logical and probabilistic interactions between large numbers of objects. This level of expressivity comes at the cost of increased complexity of inference, motivating a new line of research in lifted probabilistic inference. By exploiting symmetries of the relational structure in the model, and reasoning about ...

Given the increasing amount of neuroimaging studies, there is a growing need to summarize published results. Coordinate-based meta-analyses use the locations of statistically significant local maxima with possibly the associated effect sizes to aggregate studies. In this paper, we investigate the influence of key characteristics of a coordinate-based meta-analysis on (1) the balance between false and true positives and (2) the activation ...

Scholars of mobilisation and policy influence employ two quite different approaches to mapping interest group systems. Those interested in research questions on mobilisation typically rely on a bottom-up mapping strategy in order to characterise the total size and composition of interest group communities. Researchers with an interest in policy influence usually rely on a top-down strategy in which the mapping of politically active organisations ...

Previous research has shown that the mere categorization of individuals into minimal groups will evoke in-group favoritism. The current study combines the minimal group paradigm with an ERP-experiment of spontaneous trait inferences using an expectancy-violation paradigm. 53 subjects first performed a fake reaction-time (RT) task to allow social categorization (in-group/out-group). One group of subjects (SoCat) all received the same group label ...

Despite well-established dosimetry in clinical radiotherapy, dose measurements in pre-clinical and radiobiology studies are frequently inadequate, thus undermining the reliability and reproducibility of published findings. The lack of suitable dosimetry protocols, coupled with the increasing complexity of pre-clinical irradiation platforms, undermines confidence in preclinical studies and represents a serious obstacle in the translation to ...

Mahalanobis distance (MD) is a well-known metric in multivariate analysis to separate groups or populations. In the context of the Mahalanobis-Taguchi system (MTS), a set of normal observations are used to obtain their MD values and construct a reference Mahalanobis distance space, for which a suitable classification threshold can then be introduced to classify new observations as normal/abnormal. Aiming at enhancing the performance of feature ...

Teacher recommendations are an important factor in the process of track placement, but research has shown that they are biased by pupils’ social background. Pupils from higher socio-economic backgrounds are more likely to get the advice to enrol in an academic track than pupils from lower socio-economic backgrounds, irrespective of prior achievement. Previous studies looked primarily at individual pupil or parent characteristics and their ...

In this work, we investigate the performance of the so-called Preheat-parallel CHP configuration, for the connection to a thermal network (TN). A low-temperature geothermal source (130°C), and the connection to a 75°C/50°C and a 75°C/35°C thermal network are considered. For a pure parallel CHP configuration, the brine delivers heat to the ORC and the thermal network in parallel. However, after having delivered heat to the ORC, the brine in the ...