3 papers
stat.ML2026
Uncovering Physical Drivers of Dark Matter Halo Structures with Auxiliary-Variable-Guided Generative Models
Arkaprabha Ganguli, Anirban Samaddar, Florian Kéruzoré +4
Deep generative models (DGMs) compress high-dimensional data but often entangle distinct physical factors in their latent spaces. We present an auxiliary-variable-guided framework…
stat.ME2025
Summary Statistics of Large-scale Model Outputs for Observation-corrected Outputs
Atlanta Chakraborty, Julie Bessac
Physics-based models capture broad spatial and temporal dynamics, but often suffer from biases and numerical approximations, while observations capture localized variability but ar…
stat.ME2025
A copula-based rank histogram ensemble filter
Amit N. Subrahmanya, Julie Bessac, Andrey A. Popov +1
Serial ensemble filters implement triangular probability transport maps to reduce high-dimensional inference problems to sequences of state-by-state univariate inference problems.…