Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Abstract. Details of a new technique for obtaining rigorous results concerning the global dynamics of nonlinear systems is described. The technique abstract existence results based...
We investigate the computational complexity of an optical model of computation called the continuous space machine (CSM). We characterise worst case resource growth over time for e...
This paper introduces a new high level programming language for a novel class of computational devices namely data-procedural machines. These machines are by up to several orders o...
Abstract— Hardware implementations of Spiking Neural Networks are numerous because they are well suited for implementation in digital and analog hardware, and outperform classic ...
Benjamin Schrauwen, Michiel D'Haene, David Verstra...