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...
Process mining techniques use event data to discover process models, to check the conformance of predefined process models, and to extend such models with information about bottl...
Wil M. P. van der Aalst, Arya Adriansyah, Boudewij...
We investigate the problem of acoustic modeling in which prior language-specific knowledge and transcribed data are unavailable. We present an unsupervised model that simultaneou...
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...
This article proposes a local photometric model that compensates for specular highlights and lighting variations due to position and intensity changes. We define clearly on which ...