Bayesian principal component analysis (BPCA), a probabilistic reformulation of PCA with Bayesian model selection, is a systematic approach to determining the number of essential p...
Computational models of motivation are tools that artificial agents can use to autonomously identify, prioritize, and select the goals they will pursue. Previous research has focu...
Abstract. Designing and tuning parallel applications with MPI, particularly at large scale, requires understanding the performance implications of different choices of algorithms ...
Torsten Hoefler, William Gropp, Rajeev Thakur, Jes...
Abstract. Temporal logics are a well investigated formalism for the specification and verification of reactive systems. Using formal verification techniques, we can ensure the corr...
This paper addresses the segmentation from an image of entities that have the form of a ‘network’, i.e. the region in the image corresponding to the entity is composed of bran...