At the 9th International Summer School on AI and Big Data, Dorina Weichert (Fraunhofer IAIS) will give an Introduction to Gaussian Processes. The talk will take place on Thursday, 06.07.2023 from 3:30 p.m. – 4:30 p.m.
Talk: Introduction to Gaussian Processes
Since the early 1990s, Gaussian Processes have evolved from an unusual machine learning method to a standard tool of data scientists. Especially in regimes with small amounts of data and abstract expert knowledge, their strength becomes apparent: the combination of assumptions and data leads to particularly efficient models. Furthermore, as Bayesian models, they offer the possibility of uncertainty estimation, which can be exploited for special applications, such as Active Learning and Bayesian Optimization.
This talk introduces Gaussian Processes: first they are derived starting from simple random variables, followed by a brief introduction of the basics of kernel design. After an application example showing how the fusion of data and prior knowledge can work, I give practical tips and tricks for application.
Dorina Weichert is a mechanical engineer and works and researches at Fraunhofer IAIS in the area of Design of Experiments and Bayesian Optimization. She prefers to work with Gaussian processes, which efficiently combine a small amount of data with prior knowledge to create a trustworthy model. In her day-to-day work, she supports experts in the Industrial Analytics Team in designing experiments, analyzing data, and optimizing processes.
Read more about the 9th International Summer School on AI and Big Data.