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Identification of Hammerstein-Wiener models using Hamiltonian Monte Carlo

A Numerically Robust Bayesian Filtering Algorithm for Gaussian Mixture Models

Inferring the probability distribution over strain tensors in polycrystals from diffraction based measurements

Sequential Monte Carlo: a unified review

Variational system identification for nonlinear state-space models

A new smoothing algorithm for jump Markov linear systems

Data to Controller for Nonlinear Systems: An Approximate Solution

Memory efficient constrained optimization of scanning-beam lithography

Nonlinear System Identification: Learning while Respecting Physical Models Using a Sequential Monte Carlo Method

Parameter estimation for Jump Markov Linear Systems

A robust random matrix prediction model for extended object rotations

Beyond occam's razor in system identification: Double-descent when modeling dynamics

Deep energy-based NARX models

Stochastic quasi-Newton with line-search regularisation

A Closed-Form Prediction Update for Extended Target Tracking Using Random Matrices

Large-Amplitude Dithering Mitigates Glitches in Digital-to-Analogue Converters

Scanning laser lithography with constrained quadratic exposure optimization

Accurate Gaussian mixture model smoothing using a two-filter approach

Experimental scanning laser lithography with exposure optimization

On the construction of probabilistic Newton-type algorithms

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