Abstract. Process models provide visual support for analyzing and improving complex organizational processes. In this paper, we discuss differences of process modeling languages us...
Kathrin Figl, Jan Mendling, Mark Strembeck, Jan Re...
We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some...
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
Realistic modeling of the interaction between surgical instruments and human organs has been recognized as a key requirement in the development of high-fidelity surgical simulato...
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...