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ICML
2009
IEEE
14 years 10 months ago
Tractable nonparametric Bayesian inference in Poisson processes with Gaussian process intensities
The inhomogeneous Poisson process is a point process that has varying intensity across its domain (usually time or space). For nonparametric Bayesian modeling, the Gaussian proces...
Ryan Prescott Adams, Iain Murray, David J. C. MacK...
IPMI
2009
Springer
14 years 10 months ago
Estimating Uncertainty in Brain Region Delineations
This paper presents a method for estimating uncertainty in MRI-based brain region delineations provided by fully-automated segmentation methods. In large data sets, the uncertainty...
Karl R. Beutner, Gautam Prasad, Evan Fletcher, Cha...
SAC
2008
ACM
13 years 9 months ago
Computational methods for complex stochastic systems: a review of some alternatives to MCMC
We consider analysis of complex stochastic models based upon partial information. MCMC and reversible jump MCMC are often the methods of choice for such problems, but in some situ...
Paul Fearnhead
CVPR
2007
IEEE
14 years 11 months ago
Compositional Boosting for Computing Hierarchical Image Structures
In this paper, we present a compositional boosting algorithm for detecting and recognizing 17 common image structures in low-middle level vision tasks. These structures, called &q...
Tianfu Wu, Gui-Song Xia, Song Chun Zhu
CORR
2010
Springer
143views Education» more  CORR 2010»
13 years 10 months ago
Efficient and exact sampling of simple graphs with given arbitrary degree sequence
Uniform sampling from graphical realizations of a given degree sequence is a fundamental component in simulation-based measurements of network observables, with applications rangi...
Charo I. Del Genio, Hyunju Kim, Zoltán Toro...