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Yann McLatchie
I am a doctoral researcher at University College London in the Department of Statistical Science, supervised by Jeremias Knoblauch and Edwin Fong. Before this, I worked as a research assistant at Aalto University supervised by Aki Vehtari.
I am one of the organisers of the bi-weekly post-Bayes seminar series and the First workshop on Advances on post-Bayesian methods.
My research interests include developing theory and methodology for Bayesian prediction, and modernising prior elicitation. I have previously held data science positions at 7Bridges Ltd., GOGOX Ltd., and VoiceIQ Ltd.
Please reach out for collaboration on future projects!
Bio
- 2023 -
- PhD candidate in Statistical Science UCL Supervised by Jeremias Knoblauch and Edwin Fong
- Research visits at HKU (hosted by Edwin Fong) and Sorbonne Université (hosted by Badr-Eddine Chérief-Abdellatif)
- 2021 - 2023
- MSc Machine Learning, Data Science, and Artificial Intelligence Aalto University Thesis on "Efficient estimation of selection-induced bias in Bayesian model selection," supervised by Aki Vehtari
- Research Assistant in agile probabilistic AI Aalto University Probabilistic Machine Learning (PML) group
- 2019 - 2020
- Year abroad studying Mathematics and Computer Science Université de Bordeaux
- 2017 - 2021
- BSc (Hons) Mathematics with a Modern Language (French) University of Manchester Thesis on "Graphical models for time series analysis," supervised by Jingsong Yuan and Korbinian Strimmer
Selected research
- Yann McLatchie*, Badr-Eddine Chérief-Abdellatif*, David T. Frazier*, and Jeremias Knoblauch* (2025+). "Predictively oriented posteriors." arXiv
- Yann McLatchie, Edwin Fong, David T. Frazier, and Jeremias Knoblauch (2025). "Predictive performance of power posteriors." Biometrika. arXiv code blog talk
- David Kohns, Noa Kallioinen, Yann McLatchie, and Aki Vehtari (2025). "The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions." Bayesian Analysis. arXiv code blog
- Yann McLatchie and Aki Vehtari (2024). "Efficient estimation and correction of selection-induced bias with order statistics." Statistics and Computing. arXiv code blog
- Yann McLatchie, Sölvi Rögnvaldsson, Frank Weber, and Aki Vehtari (2024). "Advances in projection predictive inference." Statistical Science. arXiv code blog
Software
I help develop the following software:- Kulprit
- Kullback-Leibler projections for Bayesian model selection author. code
- LOO
- Approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS) contributor. code
- Projpred
- Projection predictive feature selection contributor. code
- Bambi
- Bayesian model-building interface in Python contributor. code