Privacy-preserving inference aims to avoid revealing identifying information about
individuals during inference. Lifted probabilistic inference works with groups of …

Evidence often grounds temporal probabilistic relational models over time, which makes
reasoning infeasible. To counteract groundings over time and to keep reasoning polynomial …

Lifting probabilistic graphical models and developing lifted inference algorithms aim to use
higher level groups of random variables instead of individual instances. In the past, many …

In information technology settings, multiple sensors gather data over time. With many
sensors constantly sending data, manually analysing data is infeasible. Therefore, such data …

Processes in our world are of a temporal probabilistic relational nature. An epidemic is an
example of such a process. This dissertation abstract uses the scenario of an epidemic to …

Lifted inference allows to perform inference in polynomial time wrt domain sizes. For a lifted
algorithm, completeness investigates model classes for which the algorithm is guaranteed to …

Providing decision support for questions such as" Which Patient to Treat Next?" requires a
combination of stream-based reasoning and probabilistic reasoning. The former arises due …