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IBERAMIA
2004
Springer
14 years 2 days ago
Statistical Inference in Mapping and Localization for Mobile Robots
In this paper we tackle the problem of providing a mobile robot with the ability to build a map of its environment using data gathered during navigation. The data correspond to the...
Anita Araneda, Alvaro Soto
IDA
2003
Springer
13 years 12 months ago
Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies
Abstract. Many examples exist of multivariate time series where dependencies between variables change over time. If these changing dependencies are not taken into account, any mode...
Allan Tucker, Xiaohui Liu
AAAI
1997
13 years 8 months ago
Effective Bayesian Inference for Stochastic Programs
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Daphne Koller, David A. McAllester, Avi Pfeffer
ICASSP
2011
IEEE
12 years 10 months ago
Deconvolution of neuronal signal from hemodynamic response
In this paper we describe a deconvolution technique for obtaining an approximation of the neuronal signal from an observed hemodynamic response in fMRI data. Our approach, based o...
Martin Havlicek, Jirí Jan, Milan Brazdil, V...
IPSN
2005
Springer
14 years 5 days ago
A robust architecture for distributed inference in sensor networks
— Many inference problems that arise in sensor networks require the computation of a global conclusion that is consistent with local information known to each node. A large class...
Mark A. Paskin, Carlos Guestrin, Jim McFadden