: In this paper we present our most recent work carried out in the wider context of the IST-ADRENALIN project, to facilitate formation and lifecycle management of networked enterpr...
Apostolos Vontas, Philippos Koutsakas, Christina A...
In this paper, a new method for the approximation of discrete time state-affine systems is proposed. The method is based on the diagonalization of proposed generalized controllabi...
Systems of ordinary differential equations (ODEs) are often used to model the dynamics of complex biological pathways. We construct a discrete state model as a probabilistic appro...
When using Bayesian networks, practitioners often express constraints among variables by conditioning a common child node to induce the desired distribution. For example, an ‘orâ...
We present a new approach for the discriminative training
of continuous-valued Markov Random Field (MRF)
model parameters. In our approach we train the MRF
model by optimizing t...