We present a new algorithm for probabilistic planning with no observability. Our algorithm, called Probabilistic-FF, extends the heuristic forward-search machinery of Conformant-F...
Abstract— A core challenge in probabilistic mapping is to extract meaningful uncertainty information from data registration methods. While this has been investigated in ICP-based...
Bayesian recursive inference of phase in additive Gaussian noise environments is studied. A tractable conjugate system is established using a von Mises distribution. Its shaping p...
Anthony Quinn, Jean-Pierre Barbot, Pascal Larzabal
A common task in biological research is to predict function for proteins by comparing sequences between proteins of known and unknown function. This is often done using pair-wise ...
eraction networks. In this abstract, we extend this approach by mining functional flow patterns for the purpose of detecting small-sized modules for specific functions. Methods Our...