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11\u201313 July 2022<\/strong>, Heidelberg University<\/a> and Heidelberg Institute for Theoretical Studies<\/a><\/p>\n\n\n\n

In recent years, there has been a remarkable increase in research into applying Geometry to Machine Learning problems epitomized by the upward trend of Geometric Deep Learning architectures, tools, and publications. Geometry has successfully provided diverse methods for describing the structure of data, and researchers have suggested frameworks for analyzing, unifying, and generalizing Machine Learning techniques to new settings.<\/p>\n\n\n\n

This three-day workshop will bring together researchers and practitioners of Geometry and Machine Learning to interact and exchange ideas. The workshop will consist of invited talks, including three keynotes by well-known experts. There will be two hands-on mini-courses on implementing geometric deep learning methods in Python.<\/p>\n\n\n\n

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Gyrocalculus Operations on the Space of SPD Matrices (source<\/a>)<\/figcaption><\/figure>\n\n\n\n

Confirmed Speakers<\/h2>\n\n\n\n