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20152026
most citedRandom Grid Neural Processes for Parametric Partial Differential Equations

4 citations · 9 across the 16 of their papers we have counts for

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5 papers · 1 filter

stat.CO2025

Learning Latent Variable Models via Jarzynski-adjusted Langevin Algorithm

James Cuin, Davide Carbone, O. Deniz Akyildiz

We utilise a sampler originating from nonequilibrium statistical mechanics, termed here Jarzynski-adjusted Langevin algorithm (JALA), to build statistical estimation methods in lat…

stat.CO2024

Statistical Finite Elements via Interacting Particle Langevin Dynamics

Alex Glyn-Davies, Connor Duffin, Ieva Kazlauskaite +2

In this paper, we develop a class of interacting particle Langevin algorithms to solve inverse problems for partial differential equations (PDEs). In particular, we leverage the st…

stat.CO2024

Kinetic Interacting Particle Langevin Monte Carlo

Paul Felix Valsecchi Oliva, O. Deniz Akyildiz

This paper introduces and analyses interacting underdamped Langevin algorithms, termed Kinetic Interacting Particle Langevin Monte Carlo (KIPLMC) methods, for statistical inference…

stat.CO2024

A Multiscale Perspective on Maximum Marginal Likelihood Estimation

O. Deniz Akyildiz, Michela Ottobre, Iain Souttar

In this paper, we provide a multiscale perspective on the problem of maximum marginal likelihood estimation. We consider and analyse a diffusion-based maximum marginal likelihood e…

stat.CO2023

Adaptively Optimised Adaptive Importance Samplers

Carlos A. C. C. Perello, Ömer Deniz Akyildiz

We introduce a new class of adaptive importance samplers leveraging adaptive optimisation tools, which we term AdaOAIS. We build on Optimised Adaptive Importance Samplers (OAIS), a…