Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
We consider a polymerization (fragmentation) model with size-dependent parameters involved in prion proliferation. Using power laws for the different rates of this model, we reco...
Adaptive Programming (AP) allows for the separate definition of data structures and traversals with attached computations, performed during the traversal, that operate on these dat...
Therapon Skotiniotis, Jeffrey Palm, Karl J. Lieber...
We had introduced the massively parallel global cellular automata (GCA) model. Parallel algorithms derived from applications can be mapped straight forward onto this model. In thi...
An ensemble is a set of learned models that make decisions collectively. Although an ensemble is usually more accurate than a single learner, existing ensemble methods often tend ...