References in zbMATH (referenced in 11 articles )

Showing results 1 to 11 of 11.
Sorted by year (citations)

  1. Haan, Sebastian: GeoBO: Python package for Multi-Objective Bayesian Optimisation and Joint Inversion in Geosciences (2021) not zbMATH
  2. Ambartsumyan, Ilona; Boukaram, Wajih; Bui-Thanh, Tan; Ghattas, Omar; Keyes, David; Stadler, Georg; Turkiyyah, George; Zampini, Stefano: Hierarchical matrix approximations of Hessians arising in inverse problems governed by PDEs (2020)
  3. Constantinescu, Emil M.; Petra, Noémi; Bessac, Julie; Petra, Cosmin G.: Statistical treatment of inverse problems constrained by differential equations-based models with stochastic terms (2020)
  4. Jha, Prashant K.; Cao, Lianghao; Oden, J. Tinsley: Bayesian-based predictions of COVID-19 evolution in Texas using multispecies mixture-theoretic continuum models (2020)
  5. Koval, Karina; Alexanderian, Alen; Stadler, Georg: Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs (2020)
  6. Vuchkov, Radoslav G.; Petra, Cosmin G.; Petra, Noémi: On the derivation of quasi-Newton formulas for optimization in function spaces (2020)
  7. Chen, Peng; Villa, Umberto; Ghattas, Omar: Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty (2019)
  8. Crestel, Benjamin; Stadler, Georg; Ghattas, Omar: A comparative study of structural similarity and regularization for joint inverse problems governed by PDEs (2019)
  9. Lan, Shiwei: Adaptive dimension reduction to accelerate infinite-dimensional geometric Markov chain Monte Carlo (2019)
  10. Attia, Ahmed; Alexanderian, Alen; Saibaba, Arvind K.: Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems (2018)
  11. Chen, Peng; Villa, Umberto; Ghattas, Omar: Hessian-based adaptive sparse quadrature for infinite-dimensional Bayesian inverse problems (2017)