Workshop on Uncertainty Propagation in Composite Models

Abstract

Together with Carl Henrik Ek and Neill Campbell, I organized a workshop on uncertainty propagation in composite models at the Siemens AI Lab. This workshop will focused on three aspects of machine learning: (i) how to propagate uncertainty through composite models, (ii) how to interpret a composite probability distribution and (iii) how to evaluate success. Inspired by reinforcement learning we wanted to encourage a discussion and debate on what abstract tasks can be constructed that would provide an interpretable measure of success.

Markus Kaiser

Research Scientist

Research Associate at the University of Cambridge and Research Scientist at Siemens AG. I am interested in scalable Bayesian machine learning and Gaussian processes.