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» Optimal Nonlinear Prediction of Random Fields on Networks
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LION
2009
Springer
135views Optimization» more  LION 2009»
14 years 2 months ago
Neural Network Pairwise Interaction Fields for Protein Model Quality Assessment
We present a new knowledge-based Model Quality Assessment Program (MQAP) at the residue level which evaluates single protein structure models. We use a tree representation of the ...
Alberto J. M. Martin, Alessandro Vullo, Gianluca P...
ICML
2003
IEEE
14 years 8 months ago
Semi-Supervised Learning Using Gaussian Fields and Harmonic Functions
An approach to semi-supervised learning is proposed that is based on a Gaussian random field model. Labeled and unlabeled data are represented as vertices in a weighted graph, wit...
Xiaojin Zhu, Zoubin Ghahramani, John D. Lafferty
FLAIRS
2004
13 years 9 months ago
Backcalculation of Airport Flexible Pavement Non-Linear Moduli Using Artificial Neural Networks
The Heavy Weight Deflectometer (HWD) test is one of the most widely used tests for assessing the structural integrity of airport pavements in a non-destructive manner. The elastic...
Kasthurirangan Gopalakrishnan, Marshall R. Thompso...
CIDM
2007
IEEE
14 years 1 months ago
Application of Neural Networks for Data Modeling of Power Systems with Time Varying Nonlinear Loads
— Nowadays power distribution systems typically operate with nonsinusoidal voltages and currents. Harmonic currents from nonlinear loads propagate through the system and cause ha...
Joy Mazumdar, Ganesh K. Venayagamoorthy, Ronald G....
CORR
2008
Springer
167views Education» more  CORR 2008»
13 years 7 months ago
Energy Scaling Laws for Distributed Inference in Random Networks
The energy scaling laws of multihop data fusion networks for distributed inference are considered. The fusion network consists of randomly located sensors independently distributed...
Animashree Anandkumar, Joseph E. Yukich, Lang Tong...