Regime switching models, in which the state of the world is locally stationary, are a useful abstraction for many continuous valued data streams. In this paper we develop an onlin...
Gordon J. Ross, Dimitris K. Tasoulis, Niall M. Ada...
Given a data layout of a large walkthrough scene, we present a novel and simple spatial hierarchy on the disk-pages of the layout that has notable advantages over a conventional s...
Behzad Sajadi, Yan Huang, Pablo Diaz-Gutierrez, Su...
Energy-based learning (EBL) is a general framework to describe supervised and unsupervised training methods for probabilistic and non-probabilistic factor graphs. An energy-based ...
— Perceptual aliasing makes topological navigation a difficult task. In this paper we present a general approach for topological SLAM (simultaneous localisation and mapping) whi...
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...