Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Visual modeling languages for discrete behavior modeling allow the modeler to describe how systems develop over time during system runs. Models of these languages are the basis fo...
Enrico Biermann, Claudia Ermel, Jonas Hurrelmann, ...
In conservation biology and natural resource management, adaptive management is an iterative process of improving management by reducing uncertainty via monitoring. Adaptive manag...
Iadine Chades, Josie Carwardine, Tara G. Martin, S...
We present an objective approach for evaluating probability elicitation methods in probabilistic models. Our method draws on ideas from research on learning Bayesian networks: if ...
Log-linear parsing models are often trained by optimizing likelihood, but we would prefer to optimise for a task-specific metric like Fmeasure. Softmax-margin is a convex objecti...