The Bayesian Reading Group is a series of weekly informal meetings held at the Department of Statistics, typically during term. The aim of the reading group is to create a friendly environment where we can learn about each other’s work, exchange ideas, and generally broaden our knowledge of the literature and the current research in Bayesian Statistics.
In each meeting, a presentation is given by one of the participants about a topic of their choice, including their own current work, a paper they have read and found interesting, or a literature overview.
The common theme of the presentations is ‘Bayesian statistics’, and many of the past presentations have touched on various aspects of the methodology and theory of the Bayesian approach, often in the nonparametric setting. Alongside this main theme, other related topics are certainly welcome as well. The meetings are typically one hour long, including the time for questions and discussions on the presentation.
We typically meet on Tuesday afternoons, and to encourage attendance, we hold the reading group in hybrid format, with in-person meetings at the Department of Statistics and a zoom link for those wishing to join online.
We hope to see you there! To join the reading group, learn more, and for any question in general, please do not hesitate to contact Matteo.
Tuesday 17 January, 4pm - 5pm: Matteo Giordano, Adaptive Inference Over Besov Spaces in the White Noise Model Using p-Exponential Priors, by Agapiou and Savva (arXiv preprint, 2022)
Tuesday 24 January, 4pm - 5pm: Paul Rosa, Stationary Kernels and Gaussian Processes on Lie Groups and Their Homogeneous Spaces I: the Compact Case, by Azangulov et al. (arXiv, 2022)
Tuesday 31 January, 4pm - 5pm: Judith Rousseau, Minimax Rate of Distribution Estimation on Unknown Submanifold under Adversarial Losses, by Tang and Yang (arXiv, 2022)
Tuesday 7 February, 4pm - 5pm: Deborah Sulem, TBA
Tuesday 14 February, 4pm - 5pm: TBA
Tuesday 21 February, 4pm - 5pm: TBA
Tuesday 28 February, 4pm - 5pm: TBA
Recent past meetings
Tuesday 6 December, 4pm - 5pm: We will attend the Bayesian Analysis webinar for the discussion on the paper Deep Gaussian Processes for Calibration of Computer Models (Bayesian Analysis, 2022), by S. Marmin and M. Filippone.
Tuesday 29 November, 3.30pm - 4.40pm: Caroline Lawless, Clustering Consistency with Dirichlet Process Mixtures, by Ascolani et al. (arXiv preprint, 2022)
Tuesday 22 November, 3.30pm - 4.40pm: Judith Rousseau, Martingale Posterior Distributions, by Fong, Holmes and Walker (JRSSB, 2022)
Tuesday 8 November, 3.30pm - 4.40pm: Paul Rosa, Posterior Asymptotics in Wasserstein Metrics on the Real Line, by Chae, De Blasi and Walker (Electronic J. Statistics, 2021)
Wednesday 26 October 2022, 2pm - 3.30pm: We will attend the departmental seminar by Jianqing Fan (Princeton University) on Factor Augmented Sparse Throughput Deep ReLu Neural Networks for High Dimensional Regression
Wednesday 19 October 2022, 3.30pm - 4.30pm: Deborah Sulem, Variational Bayes Methods for Temporal Point Processes
Wednesday 5 October 2022, 4pm - 5pm: Matteo Giordano, Coverage of Credible Intervals in Nonparametric Monotone Regression, by Chakraborty and Goshal (Annals of Statistics, 2021)
Wednesday 12 October 2022, 3.30pm - 4.30pm: Daniel Moss, Differentially Private Partitioned Variational Inference, by Heikkilä et al. (arXiv preprint, 2022)