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Data Sheet 1_Convergent evolution in neural representation space: emergent order in deep belief networks.pdf
Deep Belief Networks (DBNs) learn hierarchical generative models without class supervision. We ask how this unsupervised hierarchy reorganizes data, whether it exposes latent class structure, and whether independently initialized networks discover corresponding internal representations. Across MN
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