Uncertainty is a popular phenomenon in machine learning and a variety of methods to model uncertainty at different levels has been developed. The aim of this paper is to motivate ...
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Ubiquitous access to sophisticated internet services from diverse end devices across heterogeneous networks requires the injection of additional functionality into the network to ...
In this paper, we demonstrate that the main standard optimization techniques dependency directed backtracking and model merging can be adapted to description logics with concrete ...
In this paper, we propose a stochastic simulation to model and analyze cellular signal transduction. The high number of objects in a simulation requires advanced visualization tec...
Martin Falk, Michael Klann, Matthias Reuss, Thomas...