Due to physiological variation, patients diagnosed with the same condition may exhibit divergent, but related, responses to the same treatments. Hidden Parameter Markov Decision Processes (HiP-MDPs) tackle this transfer-learning problem by embedding these tasks into a low-dimensional space. However, the original formulation of HiP-MDP had a critical flaw: the embedding uncertainty was modelled ...

Certain problems in which a cooled rigid punch indents an elastic half-space have no steady state solution. A simple model is described in which it is shown that this paradox is avoided by the assumption of a thermal resistance varying inversely with contact pressure. A limiting case of this system retains linearity and introduces a state of "imperfect" contact in which contact pressure is negl...

This paper integrates our contributions in the domain of blind source separation (BSS) and blind source deconvolution (BSD) both in static and dynamic environments. We focus on the use of the state space formulation and the development of a generalized optimization framework, using Kullback-Liebler divergence as the performance measure subject to the constraints of a state space representation....

This article presents a unified state-space model for ship maneuvering, station-keeping, and control in a seaway. The frequency-dependent potential and viscous damping terms, which in classic theory results in a convolution integral not suited for real-time simulation, is compactly represented by using a state-space formulation. The separation of the vessel model into a low-frequency model (rep...

Timber production in New Zealand was privatized in 1987. We examine the effects of this change on the level of New Zealand sawn timber production, and changes in the seasonal pattern, using a state-space model with intervention variables. We describe the formulation and estimation of the state-space model, and show how it can be used to examine both the structural changes around the time of pri...

In this paper an optimal control problem is considered, where the control variable lies in a measure space and the state variable fulfills an elliptic equation. This formulation leads to a sparse structure of the optimal control. In this setting we prove a new regularity result for the optimal state and the optimal control. Moreover, a finite element discretization based on [E. Casas, C. Clason...

A Lagrangian-Hamiltonian variational formulation is proposed for the thermoelasticity of heat conductors and its generalization to anelasticity described by means of internal-state variablesby using a gauge-theoretical technique (introduction of an additional variable of state the gradient of thermacy that renders the system apparently Hamiltonian). Projecting the equations resulting from the E...

We provide a language for formulating a range of state space models with response densities within the exponential family. The described methodology is implemented in the R-package sspir. A state space model is specified similarly to a generalized linear model in R, and then the time-varying terms are marked in the formula. Special functions for specifying polynomial time trends, harmonic seaso...

The analysis follows an earlier paper Brown (2003) which analysed a moving disturbance using a directed cyclic graph defined as Interrelated Fluctuating Entities (IFEs) of /STATE/, /SPACE/, /αTIME/, /βTIME/. This paper provides a statistical analysis of the alternative positions in space and state of an IFE for a defined total time magnitude. The probability for a freely moving entity interacti...