Abstract. We propose a novel probabilistic framework to merge information from DWI tractography and resting-state fMRI correlations. In particular, we model the interaction of late...
Archana Venkataraman, Yogesh Rathi, Marek Kubicki,...
We propose a probabilistic factorial sparse coder model for single channel source separation in the magnitude spectrogram domain. The mixture spectrogram is assumed to be the sum ...
Robert Peharz, Michael Stark, Franz Pernkopf, Yann...
Advanced wireless sensor network algorithms pose challenges to their formal modeling and analysis, such as modeling probabilistic and real-time behaviors and novel forms of commun...
The most often used approaches to obtaining and using residuals in applied work with time series models, are unified and documented with both partially-known and new features. Spe...
Variational Bayesian Expectation-Maximization (VBEM), an approximate inference method for probabilistic models based on factorizing over latent variables and model parameters, has ...