When dealing with computationally expensive simulation codes or process measurement data, surrogate modeling methods are firmly established as facilitators for design space explor...
Dirk Gorissen, Ivo Couckuyt, Eric Laermans, Tom Dh...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Software code caches are increasingly being used to amortize the runtime overhead of dynamic optimizers, simulators, emulators, dynamic translators, dynamic compilers, and other t...
Derek Bruening, Vladimir Kiriansky, Timothy Garnet...
Recent advances in space and computer technologies are revolutionizing the way remotely sensed data is collected, managed and interpreted. In particular, NASA is continuously gath...
The high degree of complexity and autonomy of future robotic space missions, such as Mars Science Laboratory (MSL), poses serious challenges in assuring their reliability and ef...