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cs.LG2026
Instance-Adaptive Parametrization for Amortized Variational Inference
Andrea Pollastro, Andrea Apicella, Francesco Isgrò +1
Variational autoencoders (VAEs) rely on amortized variational inference to enable efficient posterior approximation, but this efficiency comes at the cost of a shared parametrizati…
cs.LG2026★ 1 cited
Don't stop me now: Rethinking Validation Criteria for Model Parameter Selection
Andrea Apicella, Francesco Isgrò, Andrea Pollastro +1
Despite the extensive literature on training loss functions, the evaluation of generalization on the validation set remains underexplored. In this work, we conduct a systematic emp…