In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
This paper concerns the characterization of clouds on meteorological satellite image sequences through points trajectories. These temporal curves can be computed from the result o...
We present a probabilistic approach to shape matching which is invariant to rotation, translation and scaling. Shapes are represented by unlabeled point sets, so discontinuous bou...
Abstract. Business process (BP) modeling is a building block for design and management of business processes. Two fundamental aspects of BP modeling are: a formal framework that we...
Kamal Bhattacharya, Cagdas Evren Gerede, Richard H...