University of Cambridge > > Machine Learning Reading Group @ CUED > Probabilistic Numerics

Probabilistic Numerics

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Alessandro Davide Ialongo.


After a brief conceptual review of aims and tools, we will cover the Probabilistic Numerical approach to quadrature (integration) and optimisation (quasi-newton methods and stochastic gradient descent).


There is no required reading, however Persi Diaconis’ 1988 paper Bayesian Numerical Analysis provides a good, historical introduction to the subject matter of probabilistic numerics.

This talk is part of the Machine Learning Reading Group @ CUED series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


© 2006-2024, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity