activity
20182020
most citedVarGrad: A Low-Variance Gradient Estimator for Variational Inference

2 citations · 2 across the 1 of their papers we have counts for

collaborators

5 papers

stat.ML20202 cited

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…

stat.ME2020

Generalized Bayesian Filtering via Sequential Monte Carlo

Ayman Boustati, Ömer Deniz Akyildiz, Theodoros Damoulas +1

We introduce a framework for inference in general state-space hidden Markov models (HMMs) under likelihood misspecification. In particular, we leverage the loss-theoretic perspecti…

stat.CO2019

Convergence rates for optimised adaptive importance samplers

Ömer Deniz Akyildiz, Joaquín Míguez

Adaptive importance samplers are adaptive Monte Carlo algorithms to estimate expectations with respect to some target distribution which \textit{adapt} themselves to obtain better…

math.OC2018

A probabilistic incremental proximal gradient method

Ömer Deniz Akyildiz, Émilie Chouzenoux, Víctor Elvira +1

In this paper, we propose a probabilistic optimization method, named probabilistic incremental proximal gradient (PIPG) method, by developing a probabilistic interpretation of the…

stat.CO2018

The Incremental Proximal Method: A Probabilistic Perspective

Ömer Deniz Akyildiz, Victor Elvira, Joaquin Miguez

In this work, we highlight a connection between the incremental proximal method and stochastic filters. We begin by showing that the proximal operators coincide, and hence can be r…