28 citations · 41 across the 10 of their papers we have counts for
3 papers · 1 filter
How Neural Losses Shape VAE Latents
Giorgio Strano, Luca Cerovaz, Michele Mancusi +2
Modern VAEs are rarely trained with the pointwise likelihood implied by the standard -VAE objective. In practice, pointwise reconstruction is often combined with perceptual and…
Latent Autoregressive Source Separation
Emilian Postolache, Giorgio Mariani, Michele Mancusi +3
Autoregressive models have achieved impressive results over a wide range of domains in terms of generation quality and downstream task performance. In the continuous domain, a key…
Unsupervised Source Separation via Bayesian Inference in the Latent Domain
Michele Mancusi, Emilian Postolache, Giorgio Mariani +4
State of the art audio source separation models rely on supervised data-driven approaches, which can be expensive in terms of labeling resources. On the other hand, approaches for…