Dynamic probabilistic networks are a compact representation of complex stochastic processes. In this paper we examine how to learn the structure of a DPN from data. We extend stru...
The tree constraint partitions a directed graph into node-disjoint trees. In many practical applications that involve such a partition, there exist side constraints specifying requ...
Automatic differentiation is a semantic transformation that applies the rules of differential calculus to source code. It thus transforms a computer program that computes a mathema...
Christian H. Bischof, Paul D. Hovland, Boyana Norr...
Reasoning about graph and model transformation systems is an important means to underpin model-driven software engineering, such as Model-Driven Architecture (MDA) and Model Integ...
In this paper we describe a method for creating sharp features and trim regions on multiresolution subdivision surfaces along a set of user-defined curves. Operations such as engr...
Henning Biermann, Ioana M. Martin, Denis Zorin, Fa...