mailitics

Tag: parametric

  • Parametric RDT approach to computational gap of symmetric binary perceptron

    Parametric RDT approach to computational gap of symmetric binary perceptron arXiv:2601.10628v1 Announce Type: new Abstract: We study potential presence of statistical-computational gaps (SCG) in symmetric binary perceptrons (SBP) via a parametric utilization of emph{fully lifted random duality theory} (fl-RDT) [96]. A structural change from decreasingly to arbitrarily ordered $c$-sequence (a key fl-RDT parametric component) is…

  • Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference

    Active learning for data-driven reduced models of parametric differential systems with Bayesian operator inference arXiv:2601.00038v1 Announce Type: new Abstract: This work develops an active learning framework to intelligently enrich data-driven reduced-order models (ROMs) of parametric dynamical systems, which can serve as the foundation of virtual assets in a digital twin. Data-driven ROMs are explainable, computationally…

  • Adaptive Nonparametric Perturbations of Parametric Bayesian Models

    Adaptive Nonparametric Perturbations of Parametric Bayesian Models arXiv:2412.10683v2 Announce Type: cross Abstract: Parametric Bayesian modeling offers a powerful and flexible toolbox for scientific data analysis. Yet the model, however detailed, may still be wrong, and this can make inferences untrustworthy. In this paper we study nonparametrically perturbed parametric (NPP) Bayesian models, in which a parametric…