13 citations · 30 across the 16 of their papers we have counts for
4 papers · 1 filter
Decoder ensembling for learned latent geometries
Stas Syrota, Pablo Moreno-Muñoz, Søren Hauberg
Latent space geometry provides a rigorous and empirically valuable framework for interacting with the latent variables of deep generative models. This approach reinterprets Euclide…
On Masked Pre-training and the Marginal Likelihood
Pablo Moreno-Muñoz, Pol G. Recasens, Søren Hauberg
Masked pre-training removes random input dimensions and learns a model that can predict the missing values. Empirical results indicate that this intuitive form of self-supervised l…
Revisiting Active Sets for Gaussian Process Decoders
Pablo Moreno-Muñoz, Cilie W Feldager, Søren Hauberg
Decoders built on Gaussian processes (GPs) are enticing due to the marginalisation over the non-linear function space. Such models (also known as GP-LVMs) are often expensive and n…
Reliable training and estimation of variance networks
Nicki S. Detlefsen, Martin Jørgensen, Søren Hauberg
We propose and investigate new complementary methodologies for estimating predictive variance networks in regression neural networks. We derive a locally aware mini-batching scheme…