We present a class of models that, via a simple construction,
enables exact, incremental, non-parametric, polynomial-time,
Bayesian inference of conditional measures. The approac...
— Probabilistic sampling-based motion planners are unable to detect when no feasible path exists. A common heuristic is to declare a query infeasible if a path is not found in a ...
Kris K. Hauser, Timothy Bretl, Jean-Claude Latombe
Background: In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons an...
Abstract. Mechanical ventilation can cause severe lung damage by inadequate adjustment of the ventilator. We introduce a Machine Learning approach to predict the pressure-dependent...
The prediction of the native structures of proteins, the socalled protein folding problem, is a NP hard multi-minima optimization problem for which to date no routine solutions ex...