Showing items 1 - 20 of 37

Predicting political violence using a state-space model

A heteroscedastic likelihood model for two-frame optical flow

Clinical Decision Support Tools for Predicting Outcomes in Patients Undergoing Total Knee Arthroplasty: A Systematic Review

Gaussian Variational State Estimation for Nonlinear State-Space Models

Variational State and Parameter Estimation

A fast quasi-Newton-type method for large-scale stochastic optimisation

Bayesian non-parametric Bragg-edge fitting for neutron transmission strain imaging

Constrained subspace method for the identification of structured state-space models (COSMOS)

Implementation of traction constraints in Bragg-edge neutron transmission strain tomography

Affinely parametrized state-space models: ways to maximize the likelihood function

Constructing Metropolis-Hastings proposals using damped BFGS updates

Probabilistic modelling and reconstruction of strain

Sparse Bayesian ARX models with flexible noise distributions

Development of a planning tool for network ancillary services using customer-owned solar and battery storage

Linearly constrained Gaussian processes

Smoothed state estimation via efficient solution of linear equations

A nonlinear programming approach to exposure optimization in scanning laser lithography

Identification of Hammerstein-Wiener models

Recovering the spectrum of a low level signal from two noisy measurements using the cross power spectral density

UNIT: a freely available system identification toolbox

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