This paper addresses the probabilistic inference of geometric structures from images. Specifically, of synthesizing range data to enhance the reconstruction of a 3D model of an in...
Reasoning about space has been a considerable field of study both in Artificial Intelligence and in spatial information theory. Many applications benefit from the inference of ...
We present two alternative mappings between a macroscopic neural mass model and a reduction of a conductance-based model. These provide possible explanations of the relationship b...
Serafim Rodrigues, Anton V. Chizhov, Frank Marten,...
Features have been widely used by the product line community to model variability. They represent the common and variable characteristics of the members of a product line. They ar...
Abstract. Between-Pathway Models (BPMs) are network motifs consisting of pairs of putative redundant pathways. In this paper, we show how adding another source of high-throughput d...
Benjamin J. Hescott, Mark D. M. Leiserson, Lenore ...