Author

Raphael Huser

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Preprint Oct 2026

Spatial Prediction with Guided Diffusion

Spatial prediction is a critically important task in data analyses that involve spatially or spatio-temporally-referenced data. It is commonly carried out using hierarchical models, which comprise a process model describing the latent process of interest, and a data model describing how the process is observed. The tar...

Andrew Zammit-Mangion, L. Astfalck, Raphael Huser et al. · 0 citations

Sep 2026

Quantifying Ground-Motion Variability from Rupture Uncertainty: How Many Simulations Are Enough?

Probabilistic seismic hazard assessment (PSHA) increasingly leverages physics-based simulations (PBS) to improve the representation of source, site, and path effects, particularly in regions with limited observational data. Source parameters exert a strong influence on ground-motion intensity, underscoring the need f...

D. Castro-Cruz, Tariq Anwar Aquib, S. Nik et al. · Bulletin of The Seismologica... · 1 citation

#machine learning Preprint Sep 2026

Uncertainty and Explainability in Deep Rough Volatility: A Neural Information-Theoretic Posterior Approach

A simulation-based inference framework for rough Heston (rHeston) calibration that learns the posterior distribution of the model parameters conditional on an IV surface and introduces Hellinger-SHAP, an information-theoretic explainability method for posterior inference.

D. Brigo, Raphael Huser, Dan Leonte · 0 citations