Recursive neural networks are a powerful tool for processing structured data. According to the recursive learning paradigm, the input information consists of directed positional ac...
Monica Bianchini, Marco Gori, Lorenzo Sarti, Franc...
In recent years, overlay networks have become an effective alternative to IP multicast for efficient point to multipoint communication across the Internet. Typically, nodes self-...
Dejan Kostic, Adolfo Rodriguez, Jeannie R. Albrech...
The study of gene function is critical in various genomic and proteomic fields. Due to the availability of tremendous amounts of different types of protein data, integrating thes...
Xiaoyu Jiang, Naoki Nariai, Martin Steffen, Simon ...
The probabilistic network technology is a knowledgebased technique which focuses on reasoning under uncertainty. Because of its well defined semantics and solid theoretical founda...
We present two Bayesian algorithms CD-B and CD-H for discovering unconfounded cause and effect relationships from observational data without assuming causal sufficiency which prec...
Subramani Mani, Constantin F. Aliferis, Alexander ...