During the last decade, the study of large scale complex networks has attracted a substantial amount of attention and works from several domains: sociology, biology, computer scie...
Antoine Scherrer, Pierre Borgnat, Eric Fleury, Jea...
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...
In the statistical approach for self-organizing maps (SOMs), learning is regarded as an estimation algorithm for a Gaussian mixture model with a Gaussian smoothing prior on the ce...
We are developing a module-oriented, multiphysics, mixed-fidelity system simulation environment that will enable engineers to rapidly analyze the performance of a system and to o...
David R. Gardner, Joseph P. Castro, Paul N. Demmie...
Currently, few tools are available for assisting developers with debugging intelligent systems. Because these systems rely heavily on context dependent knowledge and sometimes sto...