References in zbMATH (referenced in 22 articles , 1 standard article )

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  1. Attia, Ahmed; Leyffer, Sven; Munson, Todd S.: Stochastic learning approach for binary optimization: application to Bayesian optimal design of experiments (2022)
  2. Ba, Yuming; de Wiljes, Jana; Oliver, Dean S.; Reich, Sebastian: Randomized maximum likelihood based posterior sampling (2022)
  3. Cao, Lianghao; Ghattas, Omar; Oden, J. Tinsley: A globally convergent modified Newton method for the direct minimization of the Ohta-Kawasaki energy with application to the directed self-assembly of diblock copolymers (2022)
  4. Kaltenbacher, Barbara; Schlintl, Anna: Fractional time stepping and adjoint based gradient computation in an inverse problem for a fractionally damped wave equation (2022)
  5. Nicholson, Ruanui; Niskanen, Matti: Joint estimation of Robin coefficient and domain boundary for the Poisson problem (2022)
  6. Povala, Jan; Kazlauskaite, Ieva; Febrianto, Eky; Cirak, Fehmi; Girolami, Mark: Variational Bayesian approximation of inverse problems using sparse precision matrices (2022)
  7. Chen, Peng; Ghattas, Omar: Taylor approximation for chance constrained optimization problems governed by partial differential equations with high-dimensional random parameters (2021)
  8. Farrell, Patrick E.; Kirby, Robert C.; Marchena-Menéndez, Jorge: Irksome: automating Runge-Kutta time-stepping for finite element methods (2021)
  9. Givoli, Dan: A tutorial on the adjoint method for inverse problems (2021)
  10. Haan, Sebastian: GeoBO: Python package for Multi-Objective Bayesian Optimisation and Joint Inversion in Geosciences (2021) not zbMATH
  11. Villa, Umberto; Petra, Noemi; Ghattas, Omar: hIPPYlib. An extensible software framework for large-scale inverse problems governed by PDEs. I: Deterministic inversion and linearized Bayesian inference (2021)
  12. 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)
  13. 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)
  14. Jha, Prashant K.; Cao, Lianghao; Oden, J. Tinsley: Bayesian-based predictions of COVID-19 evolution in Texas using multispecies mixture-theoretic continuum models (2020)
  15. Koval, Karina; Alexanderian, Alen; Stadler, Georg: Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs (2020)
  16. Reuber, Georg S.; Simons, Frederik J.: Multi-physics adjoint modeling of Earth structure: combining gravimetric, seismic, and geodynamic inversions (2020)
  17. Vuchkov, Radoslav G.; Petra, Cosmin G.; Petra, Noémi: On the derivation of quasi-Newton formulas for optimization in function spaces (2020)
  18. Chen, Peng; Villa, Umberto; Ghattas, Omar: Taylor approximation and variance reduction for PDE-constrained optimal control under uncertainty (2019)
  19. Crestel, Benjamin; Stadler, Georg; Ghattas, Omar: A comparative study of structural similarity and regularization for joint inverse problems governed by PDEs (2019)
  20. Lan, Shiwei: Adaptive dimension reduction to accelerate infinite-dimensional geometric Markov chain Monte Carlo (2019)

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