An entropy criterion on mean representations characterises the polarised regime in VAEs and related models, with theoretical links to KL minimisation and empirical tests across several architectures.
Neural Networks , volume=
2 Pith papers cite this work. Polarity classification is still indexing.
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StrEBM applies source-wise Gaussian-process-inspired energies with learnable length-scales to jointly optimize latent trajectories and observation mappings for recovering components from linear and nonlinear mixtures.
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Entropy-Based Characterisation of the Polarised Regime in Latent Variable Models
An entropy criterion on mean representations characterises the polarised regime in VAEs and related models, with theoretical links to KL minimisation and empirical tests across several architectures.
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StrEBM: A Structured Latent Energy-Based Model for Blind Source Separation
StrEBM applies source-wise Gaussian-process-inspired energies with learnable length-scales to jointly optimize latent trajectories and observation mappings for recovering components from linear and nonlinear mixtures.