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stat.ME2025
FBMS: An R Package for Flexible Bayesian Model Selection and Model Averaging
Florian Frommlet, Jon Lachmann, Geir Storvik +1
The FBMS R package facilitates Bayesian model selection and model averaging in complex regression settings by employing a variety of Monte Carlo model exploration methods. At its c…
stat.ME2025
Bayesian Generalized Nonlinear Models Offer Basis Free SINDy With Model Uncertainty
Aliaksandr Hubin
Sparse Identification of Nonlinear Dynamics (SINDy) has become a standard methodology for inferring governing equations of dynamical systems from observed data using statistical mo…
stat.ML2025
Explainable Bayesian deep learning through input-skip Latent Binary Bayesian Neural Networks
Eirik Høyheim, Lars Skaaret-Lund, Solve Sæbø +1
Modeling natural phenomena with artificial neural networks (ANNs) often provides highly accurate predictions. However, ANNs often suffer from over-parameterization, complicating in…