Space-Time Reading Group
The Space-Time Reading Group is a student-run reading group that meets weekly to discuss current topics in spatial and spatiotemporal statistics. We present papers, book chapters, or software under a theme relevant to modelling spatial phenomena. Members include Statistics graduate students as well as professors, researchers and students from across and beyond UW.
Contact: Peter Gao & John Best
Geometric Data Analysis Reading Group
Reading and discussing papers and presenting original work at the intersection of high dimensional geometry, statistics, and machine learning. Currently, the topics of interest are: Topological Data analysis -- what and how? Manifold learning algorithms, estimating the intrinsic dimension, statistical guarantees in geometric learning.
Contacts: Marina Meila & Yen-Chi Chen
Empirical Processes working group:
This working group studies empirical process methods (inequalities, limit theorems, preservation theorems) and application of these to problems in statistical theory, including semiparametric models and machine learning.
Contact: Jon Wellner
Applied, Bayesian, and Computational Statistics (ABC) Working Group:
This working group meets weekly on Fridays at 9am in Padelford C-301. Sessions feature talks and discussion about Bayesian and computational statistical methodology driven by scientific and policy-related problems.
Contact: Adrian E. Raftery