activity
20202022
most citedAttention-based Convolutional Autoencoders for 3D-Variational Data Assimilation

48 citations · 78 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20229 cited

Generalised Latent Assimilation in Heterogeneous Reduced Spaces with Machine Learning Surrogate Models

Sibo Cheng, Jianhua Chen, Charitos Anastasiou +5

Reduced-order modelling and low-dimensional surrogate models generated using machine learning algorithms have been widely applied in high-dimensional dynamical systems to improve t…

econ.EM2021

A Scalable Inference Method For Large Dynamic Economic Systems

Pratha Khandelwal, Philip Nadler, Rossella Arcucci +2

The nature of available economic data has changed fundamentally in the last decade due to the economy's digitisation. With the prevalence of often black box data-driven machine lea…

cs.CY20211 cited

Correcting public opinion trends through Bayesian data assimilation

Robin Hendrickx, Rossella Arcucci, Julio Amador Dıaz Lopez +2

Measuring public opinion is a key focus during democratic elections, enabling candidates to gauge their popularity and alter their campaign strategies accordingly. Traditional surv…

cs.LG202148 cited

Attention-based Convolutional Autoencoders for 3D-Variational Data Assimilation

Julian Mack, Rossella Arcucci, Miguel Molina-Solana +1

We propose a new 'Bi-Reduced Space' approach to solving 3D Variational Data Assimilation using Convolutional Autoencoders. We prove that our approach has the same solution as previ…

cs.LG202020 cited

Data Assimilation in the Latent Space of a Neural Network

Maddalena Amendola, Rossella Arcucci, Laetitia Mottet +5

There is an urgent need to build models to tackle Indoor Air Quality issue. Since the model should be accurate and fast, Reduced Order Modelling technique is used to reduce the dim…