Abstract. Modern incremental and iterative software engineering processes advocate to build software systems by first creating a highly simpliabstract model of the system which is ...
There is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. In this paper we develop a generative ...
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
PROFtmb predicts transmembrane beta-barrel (TMB) proteins in Gram-negative bacteria. For each query protein, PROFtmb provides both a Z-value indicating that the protein actually c...
We propose a factor-graph-based approach to joint channel-estimationand-decoding of bit-interleaved coded orthogonal frequency division multiplexing (BICM-OFDM). In contrast to ex...