This paper introduces a generic theoretical framework for predictive learning, and relates it to data-driven and learning applications in earth and environmental sciences. The iss...
Vladimir Cherkassky, Vladimir M. Krasnopolsky, Dim...
This paper proposes the use of neural network ensembles to boost the performance of a neural network based surface reconstruction algorithm. Ensemble is a very popular and powerfu...
Ioannis P. Ivrissimtzis, Yunjin Lee, Seungyong Lee...
—Biasing properly the hypothesis space of a learner has been shown to improve generalization performance. Methods for achieving this goal have been proposed, that range from desi...
Robert Thomas has shown, using simulations of experimental results, that the power flow on any line in an electric network is linearly proportional to the total system load when t...
Nodir Adilov, Thomas Light, Richard E. Schuler, Wi...
Background: The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure re...
Paolo Mereghetti, Maria Luisa Ganadu, Elena Papale...