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1:04:21
Microsoft
On Characterizing the Capacity of Neural Networks using Algebraic Topology
The learnability of different neural architectures can be characterized directly by computable measures of data complexity. In this talk, we reframe the problem of architecture selection as understanding how data determines the most expressive and generalizable architectures suited to that data, beyond inductive bias. After suggesting algebraic ...
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The Principle of Topology isn’t about shapes — it’s about how those shapes connect. 🔄✨ In topology, objects can stretch, twist, or bend — but as long as they’re not torn or glued, their fundamental properties stay the same. It’s the math that proves a coffee mug and a donut are basically twins. ☕🍩 This video is for educational purposes only. DM for credit/removal. #MathExplained #Topology #ScienceOfShapes #STEMEducation #GeometryInAction #EducationalVideo | Teachyouvids
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