Raphaël Huser

22 papers Journal 22
YearRankTypeTitle / Venue / Authors
2025 J jnl
A neural network-based adaptive cut-off approach to normality testing for dependent data.
Stat. Comput.
Minwoo Kim, Marc G. Genton, Raphaël Huser, Stefano Castruccio
2025 J jnl
Canonical Tail Dependence for Soft Extremal Clustering of Multichannel Brain Signals.
CoRR
Mara S. Talento, Jordan Richards, Raphaël Huser, Hernando Ombao
2025 J jnl
Efficient Modeling of Spatial Extremes over Large Geographical Domains.
J. Comput. Graph. Stat.
Arnab Hazra, Raphaël Huser, David Bolin
2025 J jnl
Flexible Modeling of Nonstationary Extremal Dependence using Spatially Fused LASSO and Ridge Penalties.
Technometrics
Xuanjie Shao, Arnab Hazra, Jordan Richards, Raphaël Huser
2025 J jnl
Multi-Agent Q-Learning Dynamics in Random Networks: Convergence due to Exploration and Sparsity.
CoRR
Aamal Abbas Hussain, Dan Leonte, Francesco Belardinelli, Raphaël Huser, Dario Paccagnan
2025 J jnl
Neural Bayes Estimators for Irregular Spatial Data Using Graph Neural Networks.
J. Comput. Graph. Stat.
Matthew Sainsbury-Dale, Andrew Zammit-Mangion, Jordan Richards, Raphaël Huser
2025 J jnl
Simulation-based inference via telescoping ratio estimation for trawl processes.
CoRR
Dan Leonte, Raphaël Huser, Almut E. D. Veraart
2024 J jnl
An efficient workflow for modelling high-dimensional spatial extremes.
Stat. Comput.
Silius M. Vandeskog, Sara Martino, Raphaël Huser
2024 J jnl
At the junction between deep learning and statistics of extremes: formalizing the landslide hazard definition.
CoRR
Ashok Dahal, Raphaël Huser, Luigi Lombardo
2024 J jnl
Max-convolution processes with random shape indicator kernels.
J. Multivar. Anal.
Pavel Krupskii, Raphaël Huser
2024 J jnl
Neural Bayes estimators for censored inference with peaks-over-threshold models.
J. Mach. Learn. Res.
Jordan Richards, Matthew Sainsbury-Dale, Andrew Zammit-Mangion, Raphaël Huser
2024 J jnl
Neural Methods for Amortised Parameter Inference.
CoRR
Andrew Zammit-Mangion, Matthew Sainsbury-Dale, Raphaël Huser
2024 J jnl
Partial Tail-Correlation Coefficient Applied to Extremal-Network Learning.
Technometrics
Yan Gong, Peng Zhong, Thomas Opitz, Raphaël Huser
2024 J jnl
Vecchia Likelihood Approximation for Accurate and Fast Inference with Intractable Spatial Max-Stable Models.
J. Comput. Graph. Stat.
Raphaël Huser, Michael L. Stein, Peng Zhong
2023 J jnl
Dynamic rainfall-induced landslide susceptibility: A step towards a unified forecasting system.
Int. J. Appl. Earth Obs. Geoinformation
Mahnoor Ahmed, Hakan Tanyas, Raphaël Huser, Ashok Dahal, Giacomo Titti, Lisa Borgatti, Mirko Francioni, Luigi Lombardo
2023 J jnl
Flexible and efficient spatial extremes emulation via variational autoencoders.
CoRR
Likun Zhang, Xiaoyu Ma, Christopher K. Wikle, Raphaël Huser
2022 J jnl
A unifying partially-interpretable framework for neural network-based extreme quantile regression.
CoRR
Jordan Richards, Raphaël Huser
2020 J jnl
Proteome-level assessment of origin, prevalence and function of leucine-aspartic acid (LD) motifs.
Bioinform.
Tanvir Alam, Meshari Alazmi, Rayan Naser, Franceline Huser, Afaque A. Momin, Veronica Astro, Seungbeom Hong, Katarzyna W. Walkiewicz, Christian G. Canlas, Raphaël Huser, Amal J. Ali, Jasmeen Merzaban, Antonio Adamo, Mariusz Jaremko, Lukasz Jaremko, Vladimir B. Bajic, Xin Gao, Stefan T. Arold
2018 J jnl
A comparison of dependence function estimators in multivariate extremes.
Stat. Comput.
Sabrina Vettori, Raphaël Huser, Marc G. Genton
2018 J jnl
Hierarchical Archimax copulas.
J. Multivar. Anal.
Marius Hofert, Raphaël Huser, Avinash Prasad
2017 J jnl
Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model.
Environ. Model. Softw.
Daniela Castro Camilo, Luigi Lombardo, P. Martin Mai, Jie Dou, Raphaël Huser
2016 J jnl
Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression.
IEEE Trans. Smart Grid
Souhaib Ben Taieb, Raphaël Huser, Rob J. Hyndman, Marc G. Genton