2 citations · 2 across the 2 of their papers we have counts for
3 papers · 1 filter
VarGrad: A Low-Variance Gradient Estimator for Variational Inference
Lorenz Richter, Ayman Boustati, Nikolas Nüsken +2
We analyse the properties of an unbiased gradient estimator of the ELBO for variational inference, based on the score function method with leave-one-out control variates. We show t…
Amortized variance reduction for doubly stochastic objectives
Ayman Boustati, Sattar Vakili, James Hensman +1
Approximate inference in complex probabilistic models such as deep Gaussian processes requires the optimisation of doubly stochastic objective functions. These objectives incorpora…
Non-linear Multitask Learning with Deep Gaussian Processes
Ayman Boustati, Theodoros Damoulas, Richard S. Savage
We present a multi-task learning formulation for Deep Gaussian processes (DGPs), through non-linear mixtures of latent processes. The latent space is composed of private processes…