| Stochastic spectral methods for efficient Bayesian solution of inverse problems YM Marzouk, HN Najm, LA Rahn Journal of Computational Physics 224 (2), 560-586, 2007 | 601 | 2007 |
| Simulation-based optimal Bayesian experimental design for nonlinear systems X Huan, YM Marzouk Journal of Computational Physics 232 (1), 288-317, 2013 | 521 | 2013 |
| Dimensionality reduction and polynomial chaos acceleration of Bayesian inference in inverse problems YM Marzouk, HN Najm Journal of Computational Physics 228 (6), 1862-1902, 2009 | 499 | 2009 |
| Bayesian inference with optimal maps TA El Moselhy, YM Marzouk Journal of Computational Physics 231 (23), 7815-7850, 2012 | 361 | 2012 |
| A stochastic collocation approach to Bayesian inference in inverse problems Y Marzouk, D Xiu Communications in Computational Physics 6 (4), 826-847, 2009 | 359 | 2009 |
| Sampling via measure transport: An introduction Y Marzouk, T Moselhy, M Parno, A Spantini Handbook of uncertainty quantification 1, 2, 2016 | 297* | 2016 |
| Dimension-independent likelihood-informed MCMC T Cui, KJH Law, YM Marzouk Journal of Computational Physics 304, 109-137, 2016 | 230 | 2016 |
| Data‐driven model reduction for the Bayesian solution of inverse problems T Cui, YM Marzouk, KE Willcox International Journal for Numerical Methods in Engineering 102 (5), 966-990, 2015 | 221 | 2015 |
| Large-scale inverse problems and quantification of uncertainty L Biegler, G Biros, O Ghattas, M Heinkenschloss, D Keyes, B Mallick, ... Wiley, 2011 | 219 | 2011 |
| Transport map accelerated Markov chain Monte Carlo M Parno, Y Marzouk SIAM/ASA Journal on Uncertainty Quantification 6 (2), 645–682, 2018 | 218 | 2018 |
| Adaptive Smolyak pseudospectral approximations PR Conrad, YM Marzouk SIAM Journal on Scientific Computing 35 (6), A2643-A2670, 2013 | 208 | 2013 |
| Likelihood-informed dimension reduction for nonlinear inverse problems T Cui, J Martin, YM Marzouk, A Solonen, A Spantini Inverse Problems 30 (11), 114015, 2014 | 196 | 2014 |
| Surrogate and reduced‐order modeling: a comparison of approaches for large‐scale statistical inverse problems M Frangos, Y Marzouk, K Willcox, B van Bloemen Waanders Large‐Scale Inverse Problems and Quantification of Uncertainty, 123-149, 2010 | 191 | 2010 |
| Uncertainty quantification in chemical systems HN Najm, BJ Debusschere, YM Marzouk, S Widmer, OP Le Maître International journal for numerical methods in engineering 80 (6‐7), 789-814, 2009 | 175 | 2009 |
| Optimal low-rank approximations of Bayesian linear inverse problems A Spantini, A Solonen, T Cui, J Martin, L Tenorio, Y Marzouk SIAM Journal on Scientific Computing 37 (6), A2451-A2487, 2015 | 155 | 2015 |
| Multifidelity importance sampling B Peherstorfer, T Cui, Y Marzouk, K Willcox Computer Methods in Applied Mechanics and Engineering 300, 490-509, 2016 | 152 | 2016 |
| Gradient-based stochastic optimization methods in Bayesian experimental design X Huan, YM Marzouk International Journal for Uncertainty Quantification 4 (6), 2014 | 148 | 2014 |
| Inference via low-dimensional couplings A Spantini, D Bigoni, Y Marzouk Journal of Machine Learning Research 19 (66), 1-71, 2018 | 145 | 2018 |
| A Stein variational Newton method G Detommaso, T Cui, Y Marzouk, A Spantini, R Scheichl Advances in Neural Information Processing Systems 31, 2018 | 142 | 2018 |
| Accelerating asymptotically exact MCMC for computationally intensive models via local approximations PR Conrad, YM Marzouk, NS Pillai, A Smith Journal of the American Statistical Association 111 (516), 1591-1607, 2016 | 141 | 2016 |
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