Showing 1–15 of 15 results
/ Date/ Name
Dec 18, 2025Quantile-based causal inference for spatio-temporal processes: Assessing the impacts of wildfires on US air qualityMay 18, 2025Modeling Nonstationary Extremal Dependence via Deep Spatial DeformationsMay 12, 2025Separation-based causal discovery for extremesMay 5, 2025Generative modelling of multivariate geometric extremes using normalising flowsMar 6, 2025Spectral Extremal Connectivity of Two-State Seizure Brain WavesAug 13, 2024The Efficient Tail Hypothesis: An Extreme Value Perspective on Market EfficiencyApr 14, 2024Extreme quantile regression with deep learningOct 4, 2023Neural Bayes Estimators for Irregular Spatial Data using Graph Neural NetworksAug 28, 2023Deep graphical regression for jointly moderate and extreme Australian wildfiresJul 28, 2023Extremal Dependence of Moving Average Processes Driven by Exponential-Tailed Lévy NoiseJun 27, 2023Neural Bayes estimators for censored inference with peaks-over-threshold modelsDec 4, 2022Insights into the drivers and spatio-temporal trends of extreme Mediterranean wildfires with statistical deep-learningOct 11, 2022Flexible Modeling of Nonstationary Extremal Dependence using Spatially-Fused LASSO and Ridge PenaltiesAug 16, 2022Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networksJul 27, 2019Max-and-Smooth: a two-step approach for approximate Bayesian inference in latent Gaussian models