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06/13/2023
The Rank-Reduced Kalman Filter: Approximate Dynamical-Low-Rank Filtering In High Dimensions
Inference and simulation in the context of high-dimensional dynamical sy...
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05/24/2023
Probabilistic Exponential Integrators
Probabilistic solvers provide a flexible and efficient framework for sim...
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06/17/2022
Orthonormal Expansions for Translation-Invariant Kernels
We present a general Fourier analytic technique for constructing orthono...
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02/02/2022
Fenrir: Physics-Enhanced Regression for Initial Value Problems
We show how probabilistic numerics can be used to convert an initial val...
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10/20/2021
Pick-and-Mix Information Operators for Probabilistic ODE Solvers
Probabilistic numerical solvers for ordinary differential equations comp...
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02/01/2021
A Probabilistic Taylor Expansion with Applications in Filtering and Differential Equations
We study a class of Gaussian processes for which the posterior mean, for...
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12/15/2020
Calibrated Adaptive Probabilistic ODE Solvers
Probabilistic solvers for ordinary differential equations (ODEs) assign ...
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05/17/2020
Variable Splitting Methods for Constrained State Estimation in Partially Observed Markov Processes
In this letter, we propose a class of efficient, accurate and general me...
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04/17/2020
Continuous-Discrete Filtering and Smoothing on Submanifolds of Euclidean Space
In this paper the issue of filtering and smoothing in continuous discret...
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04/01/2020
Bayesian ODE Solvers: The Maximum A Posteriori Estimate
It has recently been established that the numerical solution of ordinary...
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01/29/2020
Maximum likelihood estimation and uncertainty quantification for Gaussian process approximation of deterministic functions
Despite the ubiquity of the Gaussian process regression model, few theor...
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03/20/2019
Iterated Extended Kalman Smoother-based Variable Splitting for L_1-Regularized State Estimation
In this paper, we propose a new framework for solving state estimation p...
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10/08/2018
Probabilistic Solutions To Ordinary Differential Equations As Non-Linear Bayesian Filtering: A New Perspective
We formulate probabilistic numerical approximations to solutions of ordi...
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09/13/2018
Gaussian process classification using posterior linearisation
This paper proposes a new algorithm for Gaussian process classification ...
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05/29/2018
Iterative Statistical Linear Regression for Gaussian Smoothing in Continuous-Time Non-linear Stochastic Dynamic Systems
This paper considers approximate smoothing for discretely observed non-l...
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03/15/2017