96 citations · 202 across the 26 of their papers we have counts for
3 papers · 1 filter
Continuous-Time Bayesian Networks with Clocks
Nicolai Engelmann, Dominik Linzner, Heinz Koeppl
Structured stochastic processes evolving in continuous time present a widely adopted framework to model phenomena occurring in nature and engineering. However, such models are ofte…
Scalable Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Dominik Linzner, Michael Schmidt, Heinz Koeppl
Continuous-time Bayesian Networks (CTBNs) represent a compact yet powerful framework for understanding multivariate time-series data. Given complete data, parameters and structure…
Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data
Dominik Linzner, Heinz Koeppl
Continuous-time Bayesian networks (CTBNs) constitute a general and powerful framework for modeling continuous-time stochastic processes on networks. This makes them particularly at…