AIBullisharXiv – CS AI · Apr 106/10
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Instance-Adaptive Parametrization for Amortized Variational Inference
Researchers introduce Instance-Adaptive VAE (IA-VAE), a new framework that uses hypernetworks to generate input-specific parameter modulations for variational autoencoders, reducing the amortization gap while maintaining computational efficiency. The approach demonstrates improved posterior approximation accuracy on synthetic data and consistently better ELBO performance on image benchmarks compared to standard VAEs.