Professor for the Methods of Machine Learning at the University of Tübingen.
Jun 28, 2022 • 6 tweets • 3 min read
It’s out! Oh boy!
Probabilistic Numerics: big ideas for the internals of learning machines — and now also a BOOK, w/ @maosbot and @HansKersting!
What is #ProbabilisticNumerics, and why does it matter for ML? Thread below, with a link to a free pdf of the book at the end :)
We hear a lot about *models* in ML. But what actually happens within the “machine” during learning is a *numerical* task: Optimization (for loss minimization), Integration (for Bayesian inference), Simulation (for control, RL, physics,..). Linear Algebra for, well, everything.