3 citations · 9 across the 13 of their papers we have counts for
10 papers · 1 filter
Sampling by averaging: A multiscale approach to score estimation
Paula Cordero-Encinar, Andrew B. Duncan, Sebastian Reich +1
We introduce a novel framework for efficient sampling from complex, unnormalised target distributions by exploiting multiscale dynamics. Traditional score-based sampling methods ei…
A Proximal Newton Adaptive Importance Sampler
Víctor Elvira, Émilie Chouzenoux, O. Deniz Akyildiz
Adaptive importance sampling (AIS) algorithms are a rising methodology in signal processing, statistics, and machine learning. An effective adaptation of the proposals is key for t…
Nudging state-space models for Bayesian filtering under misspecified dynamics
Fabian Gonzalez, O. Deniz Akyildiz, Dan Crisan +1
Nudging is a popular algorithmic strategy in numerical filtering to deal with the problem of inference in high-dimensional dynamical systems. We demonstrate in this paper that gene…
Proximal Interacting Particle Langevin Algorithms
Paula Cordero Encinar, Francesca R. Crucinio, O. Deniz Akyildiz
We introduce a class of algorithms, termed proximal interacting particle Langevin algorithms (PIPLA), for inference and learning in latent variable models whose joint probability d…
Tweedie Moment Projected Diffusions For Inverse Problems
Benjamin Boys, Mark Girolami, Jakiw Pidstrigach +3
Diffusion generative models unlock new possibilities for inverse problems as they allow for the incorporation of strong empirical priors in scientific inference. Recently, diffusio…
Statistical Finite Elements via Langevin Dynamics
Ömer Deniz Akyildiz, Connor Duffin, Sotirios Sabanis +1
The recent statistical finite element method (statFEM) provides a coherent statistical framework to synthesise finite element models with observed data. Through embedding uncertain…