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Tag: surrogate

  • Bifidelity Karhunen-Lo`eve Expansion Surrogate with Active Learning for Random Fields

    Bifidelity Karhunen-Lo`eve Expansion Surrogate with Active Learning for Random Fields arXiv:2511.03756v1 Announce Type: new Abstract: We present a bifidelity Karhunen-Lo`eve expansion (KLE) surrogate model for field-valued quantities of interest (QoIs) under uncertain inputs. The approach combines the spectral efficiency of the KLE with polynomial chaos expansions (PCEs) to preserve an explicit mapping between input uncertainties…

  • SURGIN: SURrogate-guided Generative INversion for subsurface multiphase flow with quantified uncertainty

    SURGIN: SURrogate-guided Generative INversion for subsurface multiphase flow with quantified uncertainty arXiv:2509.13189v1 Announce Type: new Abstract: We present a direct inverse modeling method named SURGIN, a SURrogate-guided Generative INversion framework tailed for subsurface multiphase flow data assimilation. Unlike existing inversion methods that require adaptation for each new observational configuration, SURGIN features a zero-shot conditional generation…

  • Gaussian process surrogate with physical law-corrected prior for multi-coupled PDEs defined on irregular geometry

    Gaussian process surrogate with physical law-corrected prior for multi-coupled PDEs defined on irregular geometry arXiv:2509.02617v1 Announce Type: new Abstract: Parametric partial differential equations (PDEs) are fundamental mathematical tools for modeling complex physical systems, yet their numerical evaluation across parameter spaces remains computationally intensive when using conventional high-fidelity solvers. To address this challenge, we propose a…

  • Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AI

    Predictions as Surrogates: Revisiting Surrogate Outcomes in the Age of AI arXiv:2501.09731v1 Announce Type: new Abstract: We establish a formal connection between the decades-old surrogate outcome model in biostatistics and economics and the emerging field of prediction-powered inference (PPI). The connection treats predictions from pre-trained models, prevalent in the age of AI, as cost-effective surrogates…