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» Modelling Smooth Paths Using Gaussian Processes
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ISBI
2004
IEEE
14 years 8 months ago
A Fast Fully 4D Incremental Gradient Reconstruction Algorithm for List Mode PET Data
We present a fully four-dimensional, globally convergent, incremental gradient algorithm to estimate the continuous-time tracer density from list mode positron emission tomography...
Quanzheng Li, Evren Asma, Richard M. Leahy
ICANN
2007
Springer
14 years 1 months ago
Visualising Class Distribution on Self-organising Maps
The Self-Organising Map is a popular unsupervised neural network model which has been used successfully in various contexts for clustering data. Even though labelled data is not re...
Rudolf Mayer, Taha Abdel Aziz, Andreas Rauber
ICCAD
1997
IEEE
127views Hardware» more  ICCAD 1997»
13 years 12 months ago
OPTIMIST: state minimization for optimal 2-level logic implementation
We present a novel method for state minimization of incompletely-specified finite state machines. Where classic methods simply minimize the number of states, ours directly addre...
Robert M. Fuhrer, Steven M. Nowick
GECCO
2008
Springer
104views Optimization» more  GECCO 2008»
13 years 8 months ago
Understanding elementary landscapes
The landscape formalism unites a finite candidate solution set to a neighborhood topology and an objective function. This construct can be used to model the behavior of local sea...
Darrell Whitley, Andrew M. Sutton, Adele E. Howe
BMCBI
2008
177views more  BMCBI 2008»
13 years 7 months ago
Baseline Correction for NMR Spectroscopic Metabolomics Data Analysis
Background: We propose a statistically principled baseline correction method, derived from a parametric smoothing model. It uses a score function to describe the key features of b...
Yuanxin Xi, David M. Rocke