Abstract. Information nowadays is a capital for any organization intending to be reactive and aware of its environment. Unfortunately most modern organizations overdose on informat...
Guillaume Cabanac, Max Chevalier, Claude Chrisment...
Several real-world applications need to effectively manage and reason about large amounts of data that are inherently uncertain. For instance, pervasive computing applications mus...
Daisy Zhe Wang, Eirinaios Michelakis, Minos N. Gar...
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
This tutorial reports on the use of nonlinear dynamics in several different models of neural systems. We discuss a number of distinct approaches to neural information processing ba...