This paper addresses the problem of the optimal design of numerical experiments for the construction of nonlinear surrogate models. We describe a new method, called learner disagre...
Abstract. Probabilistic Neural Networks (PNNs) constitute a promising methodology for classification and prediction tasks. Their performance depends heavily on several factors, su...
Vasileios L. Georgiou, Sonia Malefaki, Konstantino...
Anticipation is one of the key aspects involved in flexible and adaptive behavior. The ability for an autonomous agent to extract a relevant model of its coupling with the environ...
Philippe Capdepuy, Daniel Polani, Chrystopher L. N...
Motion compensation with redundant-wavelet multihypothesis, in which multiple predictions that are diverse in transform phase contribute to a single motion estimate, is deployed i...
In the way they cope with variability, present-day methodologies are onerous, pessimistic and risky, all at the same time! Dealing with variability is an increasingly important as...