BEGIN:VCALENDAR VERSION:2.0 PRODID:researchseminars.org CALSCALE:GREGORIAN X-WR-CALNAME:researchseminars.org BEGIN:VEVENT SUMMARY:Bruno Gavranović (Strathclyde) DTSTART:20230920T090000Z DTEND:20230920T100000Z DTSTAMP:20260423T021033Z UID:CompAlg/26 DESCRIPTION:Title: Fundamental Components of Deep Learning: A category-theoretic approach\nby Bruno Gavranović (Strathclyde) as part of Machine Learning Seminar\ n\n\nAbstract\nDeep learning\, despite its remarkable achievements\, is st ill a young field. Like the early stages of many scientific disciplines\, it is permeated by ad-hoc design decisions. From the intricacies of the im plementation of backpropagation\, through new and poorly understood phenom ena such as double descent\, scaling laws or in-context learning\, to a gr owing zoo of neural network architectures - there are few unifying princip les in deep learning\, and no uniform and compositional mathematical found ation. In this talk I'll present a novel perspective on deep learning by u tilising the mathematical framework of category theory. I'll identify two main conceptual components of neural networks\, report on progress made th roughout last years by the research community in formalising them\, and sh ow how they've been used to describe backpropagation\, architectures\, and supervised learning in general\, shedding a new light on the existing fie ld.\n LOCATION:https://researchseminars.org/talk/CompAlg/26/ END:VEVENT END:VCALENDAR