Abstract

In this talk, I will review our mission to provide scalable Bayesian
inference for latent Gaussian models, and to make this claass of
models more useful. This has taken us to various places over the
years, which I will discuss. I will end presenting the newest piece in
the ``big beautiful puzzle'', a new sparse parallel direct solver for
modern architecture with GPU acceleration.