Background: Linking high-throughput experimental data with biological networks is a key step for understanding complex biological systems. Currently, visualization tools for large...
Ming Jia, Suh-Yeon Choi, Dirk Reiners, Eve Syrkin ...
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...
The ever-increasing number of intrusions in public and commercial networks has created the need for high-speed archival solutions that continuously store streaming network data to...
Francesco Fusco, Marc Ph. Stoecklin, Michail Vlach...
In this paper we report about an investigation in which we studied the properties of Bayes' inferred neural network classifiers in the context of outlier detection. The proble...