Image de couverture de livre

Separation-based causal discovery for extremes

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Jiang, Junshu, Richards, Jordan, Huser, Raphaël, Bolin, David
Format:	Preprint
Publié:	2025
Sujets:	Methodology
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks
par: Richards, Jordan, et autres
Publié: (2022)

Extreme quantile regression with deep learning
par: Richards, Jordan, et autres
Publié: (2024)

The Efficient Tail Hypothesis: An Extreme Value Perspective on Market Efficiency
par: Jiang, Junshu, et autres
Publié: (2024)

Modeling Nonstationary Extremal Dependence via Deep Spatial Deformations
par: Shao, Xuanjie, et autres
Publié: (2025)

Efficient Modeling of Spatial Extremes over Large Geographical Domains
par: Hazra, Arnab, et autres
Publié: (2021)

Generative modelling of multivariate geometric extremes using normalising flows
par: De Monte, Lambert, et autres
Publié: (2025)

Flexible Modeling of Nonstationary Extremal Dependence using Spatially-Fused LASSO and Ridge Penalties
par: Shao, Xuanjie, et autres
Publié: (2022)

Intrinsic Whittle--Matérn fields and sparse spatial extremes
par: Bolin, David, et autres
Publié: (2025)

Statistics of extremes for natural hazards: landslides and earthquakes
par: Yadav, Rishikesh, et autres
Publié: (2024)

Modeling of spatial extremes in environmental data science: Time to move away from max-stable processes
par: Huser, Raphaël, et autres
Publié: (2024)

Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks
par: Sainsbury-Dale, Matthew, et autres
Publié: (2023)

Neural Bayes estimators for censored inference with peaks-over-threshold models
par: Richards, Jordan, et autres
Publié: (2023)

Fast spatial simulation of extreme high-resolution radar precipitation data using INLA
par: Vandeskog, Silius M., et autres
Publié: (2023)

deepspat: An R package for modeling nonstationary spatial and spatio-temporal Gaussian and extremes data through deep deformations
par: Vu, Quan, et autres
Publié: (2025)

Spectral Extremal Connectivity of Two-State Seizure Brain Waves
par: Talento, Mara Sherlin D., et autres
Publié: (2025)

Joint modeling of low and high extremes using a multivariate extended generalized Pareto distribution
par: Alotaibi, Noura, et autres
Publié: (2025)

Measuring Information Transfer Between Nodes in a Brain Network through Spectral Transfer Entropy
par: Redondo, Paolo Victor, et autres
Publié: (2023)

Simulation-based inference via telescoping ratio estimation for trawl processes
par: Leonte, Dan, et autres
Publié: (2025)

Post-selection inference for causal effects after causal discovery
par: Chang, Ting-Hsuan, et autres
Publié: (2024)

Modern extreme value statistics for Utopian extremes
par: Richards, Jordan, et autres
Publié: (2023)

Neural Bayes estimation and selection for complex bivariate extremal dependence models
par: André, Lídia M., et autres
Publié: (2025)

MOPED: A moving sum method for change point detection in pairwise extremal dependence
par: McGonigle, Euan T., et autres
Publié: (2025)

Semi-parametric bulk and tail regression using spline-based neural networks
par: Majumder, Reetam, et autres
Publié: (2025)

Causal Spatial Quantile Regression
par: Gong, Yan, et autres
Publié: (2025)

Flexible and efficient emulation of spatial extremes processes via variational autoencoders
par: Zhang, Likun, et autres
Publié: (2023)

Separation-based distance measures for causal graphs
par: Wahl, Jonas, et autres
Publié: (2024)

Locally tail-scale invariant scoring rules for evaluation of extreme value forecasts
par: Olafsdottir, Helga Kristin, et autres
Publié: (2023)

Neural Conditional Simulation for Complex Spatial Processes
par: Walchessen, Julia, et autres
Publié: (2025)

Statistics of Extremes for Neuroscience
par: Redondo, Paolo V., et autres
Publié: (2024)

Assumption violations in causal discovery and the robustness of score matching
par: Montagna, Francesco, et autres
Publié: (2023)

Quantile-based causal inference for spatio-temporal processes: Assessing the impacts of wildfires on US air quality
par: Geng, Zipei, et autres
Publié: (2025)

Neural Parameter Estimation with Incomplete Data
par: Sainsbury-Dale, Matthew, et autres
Publié: (2025)

Deep learning joint extremes of metocean variables using the SPAR model
par: Mackay, Ed, et autres
Publié: (2024)

Cross-validating causal discovery via Leave-One-Variable-Out
par: Schkoda, Daniela, et autres
Publié: (2024)

Bootstrap aggregation and confidence measures to improve time series causal discovery
par: Debeire, Kevin, et autres
Publié: (2023)

Confounder-robust causal discovery and inference in Perturb-seq using proxy and instrumental variables
par: Park, Kwangmoon, et autres
Publié: (2026)

Fast and robust cross-validation-based scoring rule inference for spatial statistics
par: Olafsdottir, Helga Kristin, et autres
Publié: (2024)

A conceptual synthesis of causal assumptions for causal discovery and inference
par: Correia, Hannah E.
Publié: (2025)

An extensive simulation study evaluating the interaction of resampling techniques across multiple causal discovery contexts
par: Banerjee, Ritwick, et autres
Publié: (2025)

Deep graphical regression for jointly moderate and extreme Australian wildfires
par: Cisneros, Daniela, et autres
Publié: (2023)