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20142025
most citedLikelihood-Free Parameter Estimation with Neural Bayes Estimators

50 citations · 63 across the 10 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

stat.AP2022

Insights into the drivers and spatio-temporal trends of extreme Mediterranean wildfires with statistical deep-learning

Jordan Richards, Raphaël Huser, Emanuele Bevacqua +1

Extreme wildfires are a significant cause of human death and biodiversity destruction within countries that encompass the Mediterranean Basin. Recent worrying trends in wildfire ac…

stat.ME2022★ 3 cited

Flexible Modeling of Nonstationary Extremal Dependence using Spatially-Fused LASSO and Ridge Penalties

Xuanjie Shao, Arnab Hazra, Jordan Richards +1

Statistical modeling of a nonstationary spatial extremal dependence structure is challenging. Max-stable processes are common choices for modeling spatially-indexed block maxima, w…

stat.ME2022★ 1 cited

An Efficient Workflow for Modelling High-Dimensional Spatial Extremes

Silius M. Vandeskog, Sara Martino, Raphaël Huser

A successful model for high-dimensional spatial extremes should, in principle, be able to describe both weakening extremal dependence at increasing levels and changes in the type o…

stat.ME2022★ 50 cited

Likelihood-Free Parameter Estimation with Neural Bayes Estimators

Matthew Sainsbury-Dale, Andrew Zammit-Mangion, Raphaël Huser

Neural point estimators are neural networks that map data to parameter point estimates. They are fast, likelihood free and, due to their amortised nature, amenable to fast bootstra…

stat.ML2022★ 8 cited

Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks

Jordan Richards, Raphaël Huser

Risk management in many environmental settings requires an understanding of the mechanisms that drive extreme events. Useful metrics for quantifying such risk are extreme quantiles…

stat.AP2022

Functional-Coefficient Models for Multivariate Time Series in Designed Experiments: with Applications to Brain Signals

Paolo Victor Redondo, Raphael Huser, Hernando Ombao

To study the neurophysiological basis of attention deficit hyperactivity disorder (ADHD), clinicians use electroencephalography (EEG) which record neuronal electrical activity on t…