Summary
This r/ML post discusses whether Geometric Deep Learning (GDL) could reduce or eliminate the "brute force" pre-training common in modern deep learning. The author questions if GDL, by inherently incorporating geometric structures, might offer a more efficient way to build in invariances compared to current methods that rely on massive data and compute. This is presented as a speculative query rather than a definitive statement.
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[r/ML] [D] MYTHOS-INVERSION STRUCTURAL AUDIT
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