Abstract This paper introduces a new neural network based prior for real valued functions. Each weight and bias of the has an independent Gaussian prior, with key novelty that variances decrease in width such way resulting function is well defined limit infinite network. We show induced posterior over functions amenable to Monte Carlo sampling using Hilbert space Markov chain (MCMC) methods. ty...

Formal methods have proved their usefulness for analyzing the security of protocols. Most existingresults focus on trace properties like secrecy or authentication. There are however several securityproperties, which cannot be de ned (or cannot be naturally de ned) as trace properties and requirea notion of behavioural equivalence. Typical examples are anonymity, privacy related prop...

A recent area of interest is the development and study eigenvalue problems arising in scattering theory that may provide potential target signatures for use nondestructive testing materials. We consider a generalization electromagnetic Stekloff problem depends upon smoothing parameter, which we establish two main results were previously unavailable this type problem...