Adrian Wills

Sarah J. Johnson

CoRR, 2024

2023

Smoothed State Estimation via Efficient Solution of Linear Equations.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., October, 2023

Sequential Monte Carlo: A Unified Review.

[BibT_eX]

[DOI]

Annu. Rev. Control. Robotics Auton. Syst., May, 2023

RJHMC-Tree for Exploration of the Bayesian Decision Tree Posterior.

[BibT_eX]

[DOI]

Jodie A. Cochrane

Sarah J. Johnson

CoRR, 2023

Variational system identification for nonlinear state-space models.

[BibT_eX]

[DOI]

Autom., 2023

2022

Data to Controller for Nonlinear Systems: An Approximate Solution.

[BibT_eX]

[DOI]

Johannes N. Hendriks

James R. Z. Holdsworth

IEEE Control. Syst. Lett., 2022

A new smoothing algorithm for jump Markov linear systems.

[BibT_eX]

[DOI]

Autom., 2022

Parameter estimation for Jump Markov Linear Systems.

[BibT_eX]

[DOI]

Autom., 2022

2021

Gaussian Variational State Estimation for Nonlinear State-Space Models.

[BibT_eX]

[DOI]

Jarrad Courts

IEEE Trans. Signal Process., 2021

A Heteroscedastic Likelihood Model for Two-Frame Optical Flow.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2021

A Probabilistically Motivated Learning Rate Adaptation for Stochastic Optimization.

[BibT_eX]

[DOI]

CoRR, 2021

Stochastic quasi-Newton with line-search regularisation.

[BibT_eX]

[DOI]

Autom., 2021

A Robust Random Matrix Prediction Model for Extended Object Rotations.

[BibT_eX]

[DOI]

Nathan Bartlett

Proceedings of the 24th IEEE International Conference on Information Fusion, 2021

2020

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

[BibT_eX]

[DOI]

IEEE Trans. Signal Process., 2020

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

[BibT_eX]

[DOI]

Nathan Bartlett

Christopher Renton

IEEE Trans. Signal Process., 2020

Constrained Subspace Method for the Identification of Structured State-Space Models (COSMOS).

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2020

Variational State and Parameter Estimation.

[BibT_eX]

[DOI]

CoRR, 2020

Beyond Occam's Razor in System Identification: Double-Descent when Modeling Dynamics.

[BibT_eX]

[DOI]

CoRR, 2020

Variational Nonlinear System Identification.

[BibT_eX]

[DOI]

CoRR, 2020

Deep Energy-Based NARX Models.

[BibT_eX]

[DOI]

Johannes N. Hendriks

Fredrik K. Gustafsson

Antônio H. Ribeiro

CoRR, 2020

Practical Bayesian System Identification using Hamiltonian Monte Carlo.

[BibT_eX]

[DOI]

CoRR, 2020

Bayesian Non-parametric Bragg-edge Fitting for Neutron Transmission Strain Imaging.

[BibT_eX]

[DOI]

CoRR, 2020

Bayesian Parameter Identification for Jump Markov Linear Systems.

[BibT_eX]

[DOI]

CoRR, 2020

A Variational Expectation-Maximisation Algorithm for Learning Jump Markov Linear Systems.

[BibT_eX]

[DOI]

CoRR, 2020

Constructing a variational family for nonlinear state-space models.

[BibT_eX]

[DOI]

CoRR, 2020

Linearly Constrained Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Scanning Laser Lithography With Constrained Quadratic Exposure Optimization.

[BibT_eX]

[DOI]

IEEE Trans. Control. Syst. Technol., 2019

Learning Continuous Occupancy Maps with the Ising Process Model.

[BibT_eX]

[DOI]

Nicholas O'Dell

Christopher Renton

CoRR, 2019

Deep kernel learning for integral measurements.

[BibT_eX]

[DOI]

CoRR, 2019

Stochastic quasi-Newton with line-search regularization.

[BibT_eX]

[DOI]

CoRR, 2019

2018

Evaluating the squared-exponential covariance function in Gaussian processes with integral observations.

[BibT_eX]

[DOI]

CoRR, 2018

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

[BibT_eX]

[DOI]

Carl Jidling

CoRR, 2018

Stochastic quasi-Newton with adaptive step lengths for large-scale problems.

[BibT_eX]

[DOI]

CoRR, 2018

Accurate Gaussian Mixture Model Smoothing using a Two-Filter Approach.

[BibT_eX]

[DOI]

Proceedings of the 57th IEEE Conference on Decision and Control, 2018

2017

A Bayesian Filtering Algorithm for Gaussian Mixture Models.

[BibT_eX]

[DOI]

CoRR, 2017

Linearly constrained Gaussian processes.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

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

[BibT_eX]

[DOI]

Antonio Del Giudice

Andrew Mears

Proceedings of the 2017 IEEE PES Innovative Smart Grid Technologies Conference Europe, 2017

On the construction of probabilistic Newton-type algorithms.

[BibT_eX]

[DOI]

Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2016

A nonlinear programming approach to exposure optimization in scanning laser lithography.

[BibT_eX]

[DOI]

Proceedings of the 2016 American Control Conference, 2016

2013

Identification of Hammerstein-Wiener models.

[BibT_eX]

[DOI]

Autom., 2013

2012

Fast Linear Model Predictive Control Via Custom Integrated Circuit Architecture.

[BibT_eX]

[DOI]

Geoff Knagge

IEEE Trans. Control. Syst. Technol., 2012

2011

System identification of nonlinear state-space models.

[BibT_eX]

[DOI]

Autom., 2011

2010

Discussion on: "Generalised Linear Dynamic Factor Models: An Approach via Singular Autoregressions".

[BibT_eX]

[DOI]

Hüseyin Akçay

Eur. J. Control, 2010

Issues in sampling and estimating continuous-time models with stochastic disturbances.

[BibT_eX]

[DOI]

Lennart Ljung

Autom., 2010

Estimating state-space models in innovations form using the expectation maximisation algorithm.

[BibT_eX]

[DOI]

Proceedings of the 49th IEEE Conference on Decision and Control, 2010

Estimation of general nonlinear state-space systems.

[BibT_eX]

[DOI]

Proceedings of the 49th IEEE Conference on Decision and Control, 2010

2009

Optimal Periodic Trajectories for Band-Limited Systems.

[BibT_eX]

[DOI]

Andrew J. Fleming

IEEE Trans. Control. Syst. Technol., 2009

Maximum Likelihood Estimation of State Space Models From Frequency Domain Data.

[BibT_eX]

[DOI]

Stuart Gibson

IEEE Trans. Autom. Control., 2009

ASIC and FPGA implementation strategies for Model Predictive Control.

[BibT_eX]

[DOI]

Proceedings of the 10th European Control Conference, 2009

Nonlinear model predictive control of an inverted pendulum.

[BibT_eX]

[DOI]

Adam Mills

Proceedings of the American Control Conference, 2009

2008

Model Predictive Control Applied to Constraint Handling in Active Noise and Vibration Control.

[BibT_eX]

[DOI]

IEEE Trans. Control. Syst. Technol., 2008

Sensor Fusion for Improved Control of Piezoelectric Tube Scanners.

[BibT_eX]

[DOI]

Andrew J. Fleming

S. O. Reza Moheimani

IEEE Trans. Control. Syst. Technol., 2008

On Gradient-Based Search for Multivariable System Estimates.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2008

Maximum likelihood identification of Wiener models.

[BibT_eX]

[DOI]

Anna Hagenblad

Lennart Ljung

Autom., 2008

2007

Zames-Falb Multipliers for Quadratic Programming.

[BibT_eX]

[DOI]

IEEE Trans. Autom. Control., 2007

2005

Maximum-likelihood parameter estimation of bilinear systems.

[BibT_eX]

[DOI]

Stuart Gibson

IEEE Trans. Autom. Control., 2005

Application of MPC to an active structure using sampling rates up to 25kHz.

[BibT_eX]

[DOI]

Proceedings of the 44th IEEE IEEE Conference on Decision and Control and 8th European Control Conference Control, 2005

2004

Design of Cross-Directional Controllers with Optimal Steady State Performance.

[BibT_eX]

[DOI]

Eur. J. Control, 2004

Barrier function based model predictive control.

[BibT_eX]

[DOI]

Autom., 2004

2003

An exterior/interior-point approach to infeasibility in model predictive control.

[BibT_eX]

[DOI]

Proceedings of the 42nd IEEE Conference on Decision and Control, 2003

2002

A recentred barrier for constrained receding horizon control.

[BibT_eX]

[DOI]