Abstract. We introduce an extended computational framework for studying biological systems. Our approach combines formalization of existing qualitative models that are in wide but ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
Learning of a smooth but nonparametric probability density can be regularized using methods of Quantum Field Theory. We implement a field theoretic prior numerically, test its eff...
With power dissipation becoming an increasingly vexing problem across many classes of computer systems, measuring power dissipation of real, running systems has become crucial for...
Background: Causal networks based on the vector autoregressive (VAR) process are a promising statistical tool for modeling regulatory interactions in a cell. However, learning the...
The trend towards many-core systems comes with various issues, among them their highly dynamic and non-predictable workloads. Hence, new paradigms for managing resources of many-c...
Sebastian Kobbe, Lars Bauer, Daniel Lohmann, Wolfg...