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Bayesian

Department of Statistics

A primer on PAC-Bayesian learning *followed by* News from the PAC-Bayes frontline

Benjamin Guedj, University College London, gives a OxCSML Seminar on 26th March 2021.
Department of Statistics

MCMC for Hierachical Bayesian Models Using Non-reversible Langevin Methods

Radford M. Neal (University of Toronto), gives a talk for the department of Statistics.
Strachey Lectures

Strachey Lecture: Probabilistic machine learning: foundations and frontiers

Professor Zoubin Ghahramani gives a talk on probabilistic modelling from it's foundations to current areas of research at the frontiers of machine learning.
The Physics of Fine-Tuning

New Statistics and Prediction

In the first part of their discussion, Joe Silk and John Peacock compare approaches to statistics and how these bear on predictions in cosmology, including Weinberg’s prediction of the cosmological constant.
The Physics of Fine-Tuning

New Approaches to Probability

In the second part of their discussion, Luke Barnes and David Sloan go over the difference between frequentist and bayesian statistics, and how this difference applies to astrophysics and cosmology.
Religious Epistemology, Contextualism, and Pragmatic Encroachment

Deliberation welcomes prediction

Alan Hájek (Australian National University) gives a talk for the New Insights seminar series on 21st May 2015.

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