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Desatualizado2/05/26, 09:04 UTC31/12/31, 23:59 UTC
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KalshiRegras
A recent paper proposes an operationalization of a "Scientific Theory of Deep Learning," and argues that the field should indeed eventually admit a scientific theory.
- Though not the only possible form of a scientific theory, the paper considers the possibility that we will understand the mechanics of the learning process.
- Some desiderata they list for such a theory:
- Learning mechanics should be fundamental, proceeding logically from a first-principles description of neural network training.
- Interim assumptions about network weights, dynamics, and performance will be useful tools, but they should ultimately be explained from first principles.
- Learning mechanics should be mathematical, making unambiguous quantitative statements about important properties of neural networks.
