Precision achieved by stochastic sampling algorithms for Bayesian networks typically deteriorates in face of extremely unlikely evidence. To address this problem, we propose the E...
We propose a visualization approach for large dynamic graph structures with high degree variation and low diameter. In particular, we reduce visual complexity by multiple modes of ...
Crossdocking studies have mostly been concerned with the physical layout of a crossdock or on a single crossdock. In this work, we study a network of crossdocks taking into consid...
Ping Chen, Yunsong Guo, Andrew Lim, Brian Rodrigue...
Background: Identifying candidate genes in genetic networks is important for understanding regulation and biological function. Large gene expression datasets contain relevant info...
Anup Parikh, Eryong Huang, Christopher Dinh, Blaz ...
The variational Bayesian nonlinear blind source separation method introduced by Lappalainen and Honkela in 2000 is initialised with linear principal component analysis (PCA). Becau...
Antti Honkela, Stefan Harmeling, Leo Lundqvist, Ha...