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» Nonlinear Time-Series Prediction with Missing and Noisy Data
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BMCBI
2006
118views more  BMCBI 2006»
13 years 9 months ago
Predicting the effect of missense mutations on protein function: analysis with Bayesian networks
Background: A number of methods that use both protein structural and evolutionary information are available to predict the functional consequences of missense mutations. However, ...
Chris J. Needham, James R. Bradford, Andrew J. Bul...
AAAI
2012
11 years 11 months ago
Prediction and Fault Detection of Environmental Signals with Uncharacterised Faults
Many signals of interest are corrupted by faults of an unknown type. We propose an approach that uses Gaussian processes and a general “fault bucket” to capture a priori uncha...
Michael A. Osborne, Roman Garnett, Kevin Swersky, ...
CIDM
2007
IEEE
14 years 3 months ago
Data Mining of MISR Aerosol Product using Spatial Statistics
— In climate models, aerosol forcing is the major source of uncertainty in climate forcing, over the industrial period. To reduce this uncertainty, instruments on satellites have...
Tao Shi, Noel Cressie
3DPVT
2006
IEEE
236views Visualization» more  3DPVT 2006»
14 years 3 months ago
Multiple Camera Calibration Using Robust Perspective Factorization
In this paper we address the problem of recovering structure and motion from a large number of intrinsically calibrated perspective cameras. We describe a method that combines (1)...
Andrei Zaharescu, Radu Horaud, Rémi Ronfard...
PE
2010
Springer
138views Optimization» more  PE 2010»
13 years 7 months ago
Trace data characterization and fitting for Markov modeling
We propose a trace fitting algorithm for Markovian Arrival Processes (MAPs) that can capture statistics of any order of interarrival times between measured events. By studying re...
Giuliano Casale, Eddy Z. Zhang, Evgenia Smirni