4 citations · 5 across the 6 of their papers we have counts for
7 papers
Calibrating subgrid parametrizations of single-column ocean models via simulation-based inference
Luben M. C. Cabezas, Sacha Wendling, Aurèle Gallard +3
Subgrid parametrizations of vertical mixing in ocean models depend on free coefficients that cannot be measured directly and must be calibrated against high-fidelity references suc…
: Transformer-based inference from genomic contact maps
Eloïse Touron, Pedro L. C. Rodrigues, Julyan Arbel +2
Locating genomic features from genomic contact maps, such as centromere identification from genome-wide chromosome conformation capture techniques, notably Hi-C, can be formulated…
Theoretical guidelines for annealed Langevin dynamics in compositional simulation-based inference
Camille Touron, Gabriel V. Cardoso, Julyan Arbel +1
Compositional score-based approaches to simulation-based inference (SBI) approximate the posterior over a shared parameter given independent observations by aggregating individ…
Benchmarking Tabular Foundation Models for Conditional Density Estimation in Regression
Rafael Izbicki, Pedro L. C. Rodrigues
Conditional density estimation (CDE) - recovering the full conditional distribution of a response given tabular covariates - is essential in settings with heteroscedasticity, multi…
Simulation-Based Inference: A Practical Guide
Michael Deistler, Jan Boelts, Peter Steinbach +11
A central challenge in many areas of science and engineering is to identify model parameters that are consistent with prior knowledge and empirical data. Bayesian inference offers…
sbi reloaded: a toolkit for simulation-based inference workflows
Jan Boelts, Michael Deistler, Manuel Gloeckler +30
Scientists and engineers use simulators to model empirically observed phenomena. However, tuning the parameters of a simulator to ensure its outputs match observed data presents a…
Diffusion posterior sampling for simulation-based inference in tall data settings
Julia Linhart, Gabriel Victorino Cardoso, Alexandre Gramfort +2
Identifying the parameters of a non-linear model that best explain observed data is a core task across scientific fields. When such models rely on complex simulators, evaluating th…