Joost-Pieter Katoen demystifies probabilistic modeling
On July 13th, Professor Joost-Pieter Katoen (RWTH Aachen University) gave the final Philosophy of AI lecture: Optimistic and Pessimistic Views lecture at c:o/re, titled “Demystifying probabilistic programming“. The talk convincingly advocated the usefulness and accuracy of probabilistic inferences as performed by computers. Various types of machine learning, argued Joost-Pieter Katoen, can benefit from being developed through probabilistic programming. The underling claim is that probabilistic programs are a universal modeling formalism. Far from implying that this could result in softwares that could successfully replace humans from inferential and decision-making processes, probabilistic programming relies on correct parameterisation, which is an input provided by humans.
The c:o/re team would like to thank Professor Frederik Stjernfelt and Dr. Markus Pantsar for organizing the lecture series Philosophy of AI: Optimistic and Pessimistic Views, which ran throughout the summer semester of 2022.
Training of neural networks
Ghahramani, Zoubin. 2015. Probabilistic machine learning and artificial intelligence. Nature 521: 452–459.