|Time:||July 11 – 15, 2022|
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The Cluster of Excellence "Data-integrated Simulation Science (SimTech)" proudly announces its 1st International Summer School, taking place from July 11 – 15, 2022, with the topic
Knowledge-driven machine learning and its applications.
Despite the remarkable progress in machine learning (ML) techniques and, more generally, data-driven artificial intelligence frameworks in the last decades, most ML approaches are currently unable to extract interpretable information and knowledge from data. Moreover, predictions obtained from purely data-driven models may be physically inconsistent or even implausible. It is currently highly investigated how to include existing (expert) knowledge into the ML design to counteract these challenges. The careful integration of prior knowledge about a process, such as physical or chemical insights, into the learning procedure not only improves the quality of the learned representation but also tends to speed up the learning process with fewer data samples.
This summer school aims to equip the participants, primarily PhD researchers and early career PostDocs, with a basic understanding of how different aspects of knowledge, including but not limited to established simulation paradigms, can be induced in modern learning architectures.
A social program accompanies the scientific part.
Website of the 1st International SimTech Summer School