12 citations · 17 across the 10 of their papers we have counts for
10 papers
A Random Point Initialization Approach to Image Segmentation with Variational Level-sets
J. N. Mueller, J. N. Corcoran
Image segmentation is an essential component in many image processing and computer vision tasks. The primary goal of image segmentation is to simplify an image for easier analysis,…
Rare Events via Cross-Entropy Population Monte Carlo
Caleb Miller, Jem N. Corcoran, Michael D. Schneider
We present a Cross-Entropy based population Monte Carlo algorithm. This methods stands apart from previous work in that we are not optimizing a mixture distribution. Instead, we le…
Coupling from the Past for the Stochastic Simulation of Chemical Reaction Networks
J. N. Mueller, J. N. Corcoran
Chemical reaction networks (CRNs) are fundamental computational models used to study the behavior of chemical reactions in well-mixed solutions. They have been used extensively to…
Controlled Accuracy Gibbs Sampling of Order Constrained Non-IID Ordered Random Variates
Jem N. Corcoran, Caleb Miller
Order statistics arising from independent but not identically distributed random variables are typically constructed by arranging some , with $X_{i…
Bayesian Fusion of Data Partitioned Particle Estimates
Caleb Miller, Michael D. Schneider, Jem N. Corcoran +1
We present a Bayesian data fusion method to approximate a posterior distribution from an ensemble of particle estimates that only have access to subsets of the data. Our approach r…
A Birth and Death Process for Bayesian Network Structure Inference
D. Jennings, J. N. Corcoran
Bayesian networks (BNs) are graphical models that are useful for representing high-dimensional probability distributions. There has been a great deal of interest in recent years in…
Perfect and -Perfect Simulation Methods for the One Dimensional Kac Equation
Jem Corcoran, Dale Jennings, Paul VaughanMiller
We review the derivation of the Kac master equation model for random collisions of particles, its relationship to the Poisson process, and existing algorithms for simulating values…
Particle Filtering and Smoothing Using Windowed Rejection Sampling
J. N. Corcoran, D. Jennings
"Particle methods" are sequential Monte Carlo algorithms, typically involving importance sampling, that are used to estimate and sample from joint and marginal densities from a col…
An Efficient Search Strategy for Aggregation and Discretization of Attributes of Bayesian Networks Using Minimum Description Length
Jem Corcoran, Daniel Tran, Nicholas Levine
Bayesian networks are convenient graphical expressions for high dimensional probability distributions representing complex relationships between a large number of random variables.…
A Class Coupler for Perfect Sampling from Continuous Distributions With and Without Atoms
Wenjin Mao, Jem Corcoran
We consider the simulation of distributions that are a mixture of discrete and continuous components. We extend a Metropolis-Hastings-based perfect sampling algorithm of Corcoran a…