Outlier-robust Kalman Filtering through Generalised Bayes

1 code implementation • 9 May 2024 • Gerardo Duran-Martin, Matias Altamirano, Alexander Y. Shestopaloff, Leandro Sánchez-Betancourt, Jeremias Knoblauch, Matt Jones, François-Xavier Briol, Kevin Murphy

We derive a novel, provably robust, and closed-form Bayesian update rule for online filtering in state-space models in the presence of outliers and misspecified measurement models.

Bayesian Inference Computational Efficiency +1

Robust and Conjugate Gaussian Process Regression

1 code implementation • 1 Nov 2023 • Matias Altamirano, François-Xavier Briol, Jeremias Knoblauch

To enable closed form conditioning, a common assumption in Gaussian process (GP) regression is independent and identically distributed Gaussian observation noise.

Bayesian Inference Bayesian Optimisation +3

Robust and Scalable Bayesian Online Changepoint Detection

1 code implementation • 9 Feb 2023 • Matias Altamirano, François-Xavier Briol, Jeremias Knoblauch

This paper proposes an online, provably robust, and scalable Bayesian approach for changepoint detection.