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Physics-Inspired Binary Neural Networks: Interpretable Compression with Theoretical Guarantees

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Eamaz, Arian, Yeganegi, Farhang, Soltanalian, Mojtaba
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
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