Raphaël Huser

According to our database, Raphaël Huser authored at least 17 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2025

Multi-Agent Q-Learning Dynamics in Random Networks: Convergence due to Exploration and Sparsity.

Aamal Abbas Hussain, Dan Leonte, Francesco Belardinelli, Raphaël Huser, Dario Paccagnan

CoRR, March, 2025

A neural network-based adaptive cut-off approach to normality testing for dependent data.

Minwoo Kim, Marc G. Genton, Raphaël Huser, Stefano Castruccio

Stat. Comput., February, 2025

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

Xuanjie Shao, Arnab Hazra, Jordan Richards, Raphaël Huser

Technometrics, January, 2025

2024

An efficient workflow for modelling high-dimensional spatial extremes.

Silius M. Vandeskog, Sara Martino, Raphaël Huser

Stat. Comput., August, 2024

Partial Tail-Correlation Coefficient Applied to Extremal-Network Learning.

Yan Gong, Peng Zhong, Thomas Opitz, Raphaël Huser

Technometrics, July, 2024

Max-convolution processes with random shape indicator kernels.

Pavel Krupskii, Raphaël Huser

J. Multivar. Anal., 2024

Vecchia Likelihood Approximation for Accurate and Fast Inference with Intractable Spatial Max-Stable Models.

Raphaël Huser, Michael L. Stein, Peng Zhong

J. Comput. Graph. Stat., 2024

Neural Methods for Amortised Parameter Inference.

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

CoRR, 2024

At the junction between deep learning and statistics of extremes: formalizing the landslide hazard definition.

Ashok Dahal, Raphaël Huser, Luigi Lombardo

CoRR, 2024

2023

Dynamic rainfall-induced landslide susceptibility: A step towards a unified forecasting system.

Mahnoor Ahmed, Hakan Tanyas, Raphaël Huser, Ashok Dahal, Giacomo Titti, Lisa Borgatti, Mirko Francioni, Luigi Lombardo

Int. J. Appl. Earth Obs. Geoinformation, December, 2023

Flexible and efficient spatial extremes emulation via variational autoencoders.

Likun Zhang, Xiaoyu Ma, Christopher K. Wikle, Raphaël Huser

CoRR, 2023

2022

A unifying partially-interpretable framework for neural network-based extreme quantile regression.

Jordan Richards, Raphaël Huser

CoRR, 2022

2020

Proteome-level assessment of origin, prevalence and function of leucine-aspartic acid (LD) motifs.

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

Bioinform., 2020

2018

A comparison of dependence function estimators in multivariate extremes.

Sabrina Vettori, Raphaël Huser, Marc G. Genton

Stat. Comput., 2018

Hierarchical Archimax copulas.

Marius Hofert, Raphaël Huser, Avinash Prasad

J. Multivar. Anal., 2018

2017

Handling high predictor dimensionality in slope-unit-based landslide susceptibility models through LASSO-penalized Generalized Linear Model.

Daniela Castro Camilo, Luigi Lombardo, P. Martin Mai, Jie Dou, Raphaël Huser

Environ. Model. Softw., 2017

2016

Forecasting Uncertainty in Electricity Smart Meter Data by Boosting Additive Quantile Regression.

Souhaib Ben Taieb, Raphaël Huser, Rob J. Hyndman, Marc G. Genton

IEEE Trans. Smart Grid, 2016