Statistics Seminar

Please notice that the list below is subject to changes. The time for the seminar is 14.15 and the location is seminar room MV:F21, Skeppsgränd 3, unless otherwise noted.

1/12, Umberto Simola, University of Helsinki: Adaptive Approximate Bayesian Computation Tolerance Selection. Abstract
8/12, Magnus Röding, Chalmers and RISE: TBA
15/12, Mattias Villani, Linköping and Stockholm University: TBA

Past seminars this year:
4/2, Aleksej Zelezniak, Chalmers: Uncovering genotype-phenotype relationships using artificial intelligence. Abstract
11/2, Henrik Imberg, Chalmers: Optimal sampling in unbiased active learning. Abstract
18/2, Ottmar Cronie, Department of Public Health and Community Medicine, University of Gothenburg, and Department of Mathematics and Mathematical Statistics, Umeå University: Resample-smoothing and its application to Voronoi estimators. Abstract
10/3, Nikolaos Kourentzes, University of Skövde: Predicting with hierarchies. Abstract
17/3, Mike Pereira, Chalmers: A matrix-free approach to deal with non-stationary Gaussian random fields in geostatistical applications. Abstract
21/4, Rasmus Pedersen, Roskilde Universitet: Modelling Hematopoietic Stem Cells and their Interaction with the Bone Marrow Micro-Environment. Abstract
28/4, András Bálint, Chalmers: Mathematical methods in the analysis of traffic safety data. Abstract
16/6, Moritz Schauer, Chalmers: Trait evolution on phylogenetic trees: inference with guided Markov processes
23/6, Chris Drovandi, Queensland University of Technology, Australia: Accelerating sequential Monte Carlo with surrogate likelihoods. Abstract
6/10, Botond Szabo, University of Leiden: Variational Bayes for high-dimensional model selection
13/10, Raphaël Huser, KAUST: Estimating high-resolution Red Sea surface temperature hotspots, using a low-rank semiparametric spatial model. Abstract
20/10, Luigi Acerbi, University of Helsinki: Practical sample-efficient Bayesian inference for models with and without likelihoods. Abstract
27/10, Stéphanie van der Pas, Leiden University: Multiscale Bayesian survival analysis
24/11, Peter Jagers and Sergey Zuyev, Chalmers: Galton was right: all populations die out. Abstract
Seminars of 2019201820172016201520142013, 2012, 2011

Published: Wed 25 Nov 2020.