A weighted ℓ1-minimization approach for sparse polynomial chaos expansions J Peng, J Hampton, A Doostan Journal of Computational Physics 267, 92-111, 2014 | 150 | 2014 |

Compressive sampling of polynomial chaos expansions: Convergence analysis and sampling strategies J Hampton, A Doostan Journal of Computational Physics 280, 363-386, 2015 | 148 | 2015 |

Coherence motivated sampling and convergence analysis of least squares polynomial chaos regression J Hampton, A Doostan Computer Methods in Applied Mechanics and Engineering 290, 73-97, 2015 | 92 | 2015 |

On polynomial chaos expansion via gradient-enhanced ℓ1-minimization J Peng, J Hampton, A Doostan Journal of Computational Physics 310, 440-458, 2016 | 70 | 2016 |

Sparse polynomial chaos expansions via compressed sensing and D-optimal design P Diaz, A Doostan, J Hampton Computer Methods in Applied Mechanics and Engineering 336, 640-666, 2018 | 33 | 2018 |

Practical error bounds for a non-intrusive bi-fidelity approach to parametric/stochastic model reduction J Hampton, HR Fairbanks, A Narayan, A Doostan Journal of Computational Physics 368, 315-332, 2018 | 30 | 2018 |

Basis adaptive sample efficient polynomial chaos (BASE-PC) J Hampton, A Doostan Journal of Computational Physics 371, 20-49, 2018 | 17 | 2018 |

Compressive sampling methods for sparse polynomial chaos expansions J Hampton, A Doostan Handbook of Uncertainty Quantification, 1-29, 2016 | 17 | 2016 |

Parametric/stochastic model reduction: Low-rank representation, non-intrusive bi-fidelity approximation, and convergence analysis J Hampton, H Fairbanks, A Narayan, A Doostan arXiv preprint arXiv:1709.03661, 2017 | 9 | 2017 |

Reduced cost mission design using surrogate models JD Feldhacker, BA Jones, A Doostan, J Hampton Advances in Space Research 57 (2), 588-603, 2016 | 8 | 2016 |

Topology optimization under uncertainty using a stochastic gradient-based approach S De, J Hampton, K Maute, A Doostan Structural and Multidisciplinary Optimization, 1-24, 2020 | 7 | 2020 |

Estimation of distribution overlap of urn models J Hampton, ME Lladser PloS one 7 (11), e42368, 2012 | 5 | 2012 |

Embedded multilevel Monte Carlo for uncertainty quantification in random domains S Badia, J Hampton, J Principe arXiv preprint arXiv:1911.11965, 2019 | 4 | 2019 |

Correction: Estimation of Distribution Overlap of Urn Models J Hampton, ME Lladser PloS one 9 (1), 2014 | | 2014 |

Dissimilarity and Optimal Sampling in Urn Ensembles JD Hampton University of Colorado at Boulder, 2012 | | 2012 |

The Shifted Boundary Method: A new approach to embedded domain computations. G Scovazzi, A Main, T Song, N Atallah, O Colomés, L Nouveau, ... | | |

Embedded multilevel Monte Carlo for uncertainty quantification in complex random domains S Badia, J Hampton, J Principe | | |

Reduced Cost Maneuver Design Using Surrogate Models JD Feldhacker, BA Jones, A Doostan, J Hampton | | |