Matías Altamirano

Florence Nightingale Bicentenary Fellow  ·  University of Oxford

I’m a Florence Nightingale Bicentenary Fellow in Statistics at the University of Oxford.

Prior to this, I was a PhD Student in Statistical Science at UCL and part of the Fundamentals of Statistical Machine Learning research group supervised by Jeremias Knoblauch and François-Xavier Briol. During my PhD, I was supported by the Bloomberg Data Science PhD fellowship.

My research focuses on developing robust and reliable statistical methods and understanding their properties. I’m particularly interested in probabilistic inference and uncertainty quantification, with a focus on Bayesian methods under model misspecification.

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Matías Altamirano
News
Sep 2026

🏛️ I joined the Department of Statistics at the University of Oxford as a Florence Nightingale Bicentenary Fellow in Statistics.

Selected Publications

2026

  1. Conjugate Generalised Bayesian Inference for Discrete Doubly Intractable Problems
    William Laplante, Matias Altamirano, Jeremias Knoblauch, Andrew Duncan, François-Xavier Briol
    arXiv preprint arXiv:2511.23275, 2026
    arXiv

2025

  1. Multi-Output Robust and Conjugate Gaussian Processes
    Joshua Rooijakkers, Leiv Rønneberg, François-Xavier Briol, Jeremias Knoblauch, Matias Altamirano
    arXiv preprint arXiv:2510.26401, 2025
    arXiv
  2. Robust and Conjugate Spatio-Temporal Gaussian Processes
    William Laplante, Matias Altamirano, Andrew Duncan, Jeremias Knoblauch, François-Xavier Briol
    International Conference on Machine Learning (ICML), 2025
    arXivCode

2024

  1. Outlier-robust Kalman Filtering through Generalised Bayes
    Gerardo Durán-Martı́n, Matias Altamirano, Alexander Y Briol, Leandro Sánchez-Betancourt, Jeremias Knoblauch, Matt Jones, François-Xavier, Kevin Murphy
    International Conference on Machine Learning (ICML), 2024
    arXivCode
  2. Robust and Conjugate Gaussian Process Regression
    Matias Altamirano, François-Xavier Briol, Jeremias Knoblauch
    International Conference on Machine Learning (ICML), 2024
    arXivCode

2023

  1. Robust and Scalable Bayesian Online Changepoint Detection
    Matias Altamirano, François-Xavier Briol, Jeremias Knoblauch
    International Conference on Machine Learning (ICML), 2023
    arXivCode

2022

  1. Nonstationary multi-output Gaussian processes via harmonizable spectral mixtures
    Matias Altamirano, Felipe Tobar
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2022

Full list on Google Scholar →

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