Ahmed Attia

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All published works

Action	Title	Year	Authors
+ PDF Chat	Robust optimal design of large-scale Bayesian nonlinear inverse problems	2024	Abhijit Chowdhary Ahmed Attia Alen Alexanderian
+ PDF Chat	Heuristic algorithms for placing geomagnetically induced current blocking devices	2024	Minseok Ryu Ahmed Attia Arthur K. Barnes Russell Bent Sven Leyffer Ádám Máté
+ PDF Chat	Probabilistic Approach to Black-Box Binary Optimization with Budget Constraints: Application to Sensor Placement	2024	Ahmed Attia
+ PDF Chat	PyOED: An Extensible Suite for Data Assimilation and Model-Constrained Optimal Design of Experiments	2024	Abhijit Chowdhary Shady E. Ahmed Ahmed Attia
+	Robust A-Optimal Experimental Design for Bayesian Inverse Problems	2023	Ahmed Attia Sven Leyffer Todd Munson
+	Heuristic Algorithms for Placing Geomagnetically Induced Current Blocking Devices	2023	Minseok Ryu Ahmed Attia Arthur K. Barnes Russell Bent Sven Leyffer Ádám Máté
+	Centralized calibration of power system dynamic models using variational data assimilation	2023	Ahmed Attia Daniel Adrian Maldonado Emil M. Constantinescu Mihai Anitescu
+ PDF Chat	Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations	2022	Ahmed Attia Emil M. Constantinescu
+ PDF Chat	Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments	2022	Ahmed Attia Sven Leyffer Todd Munson
+	Stochastic Learning Approach to Binary Optimization for Optimal Design of Experiments.	2021	Ahmed Attia Sven Leyffer Todd Munson
+ PDF Chat	DATeS: a highly extensible data assimilation testing suite v1.0	2019	Ahmed Attia Adrian Sandu
+	Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems	2018	Ahmed Attia Alen Alexanderian Arvind K. Saibaba
+ PDF Chat	Cluster Sampling Filters for Non-Gaussian Data Assimilation	2018	Ahmed Attia Azam Moosavi Adrian Sandu
+	A Machine Learning Approach to Adaptive Covariance Localization	2018	Azam Moosavi Ahmed Attia Adrian Sandu
+	An Optimal Experimental Design Framework for Adaptive Inflation and Covariance Localization for Ensemble Filters	2018	Ahmed Attia Emil M. Constantinescu
+	Cluster Sampling Filters for Non-Gaussian Data Assimilation	2016	Ahmed Attia Azam Moosavi Adrian Sandu
+ PDF Chat	A Hybrid Monte‐Carlo sampling smoother for four‐dimensional data assimilation	2016	Ahmed Attia Vishwas Rao Adrian Sandu
+ PDF Chat	The reduced‐order hybrid Monte Carlo sampling smoother	2016	Ahmed Attia Răzvan Ştefănescu Adrian Sandu
+	A Hybrid Monte-Carlo Sampling Smoother for Four Dimensional Data Assimilation	2015	Ahmed Attia Vishwas Rao Adrian Sandu
+	A Sampling Filter for Non-Gaussian Data Assimilation	2014	Ahmed Attia Adrian Sandu

Common Coauthors

Coauthor	Papers Together
Adrian Sandu	8
Sven Leyffer	5
Azam Moosavi	3
Todd Munson	3
Emil M. Constantinescu	3
Minseok Ryu	2
Russell Bent	2
Ádám Máté	2
Alen Alexanderian	2
Arthur K. Barnes	2
Abhijit Chowdhary	2
Vishwas Rao	2
Daniel Adrian Maldonado	1
Shady E. Ahmed	1
Arvind K. Saibaba	1
Mihai Anitescu	1
Răzvan Ştefanescu	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	The reduced‐order hybrid Monte Carlo sampling smoother	2016	Ahmed Attia Răzvan Ştefănescu Adrian Sandu	8
+ PDF Chat	A Hybrid Monte‐Carlo sampling smoother for four‐dimensional data assimilation	2016	Ahmed Attia Vishwas Rao Adrian Sandu	7
+ PDF Chat	A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems	2016	Alen Alexanderian Noémi Petra Georg Stadler Omar Ghattas	6
+	Numerical methods for experimental design of large-scale linear ill-posed inverse problems	2008	Eldad Haber Lior Horesh Luis Tenorio	6
+	Numerical methods for A-optimal designs with a sparsity constraint for ill-posed inverse problems	2011	Eldad Haber Zhuojun Magnant Christian Lucero Luis Tenorio	5
+ PDF Chat	Efficient D-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems	2018	Alen Alexanderian Arvind K. Saibaba	5
+ PDF Chat	Simulation-based optimal Bayesian experimental design for nonlinear systems	2012	Xun Huan Youssef Marzouk	5
+	Model Variational Inverse Problems Governed by Partial Differential Equations	2011	Noei Petra Georg Stadler	5
+ PDF Chat	A-Optimal Design of Experiments for Infinite-Dimensional Bayesian Linear Inverse Problems with Regularized $\ell_0$-Sparsification	2014	Alen Alexanderian Noémi Petra Georg Stadler Omar Ghattas	5
+	Numerical methods for the design of large-scale nonlinear discrete ill-posed inverse problems	2009	Eldad Haber Lior Horesh Luis Tenorio	5
+ PDF Chat	A Computational Framework for Infinite-Dimensional Bayesian Inverse Problems Part I: The Linearized Case, with Application to Global Seismic Inversion	2013	Tan Bui‐Thanh Omar Ghattas James L. Martin Georg Stadler	4
+ PDF Chat	DATeS: a highly extensible data assimilation testing suite v1.0	2019	Ahmed Attia Adrian Sandu	4
+	Goal-oriented optimal design of experiments for large-scale Bayesian linear inverse problems	2018	Ahmed Attia Alen Alexanderian Arvind K. Saibaba	4
+ PDF Chat	Randomized algorithms for estimating the trace of an implicit symmetric positive semi-definite matrix	2011	Haim Avron Sivan Toledo	4
+ PDF Chat	Randomized matrix-free trace and log-determinant estimators	2017	Arvind K. Saibaba Alen Alexanderian Ilse C. F. Ipsen	4
+	Probabilistic Inference Using Markov Chain Monte Carlo Methods	2011	Radford M. Neal	3
+ PDF Chat	MCMC Using Hamiltonian Dynamics	2011	Radford M. Neal	3
+	Numerical Hamiltonian Problems	1994	J. M. Sanz‐Serna M. P. Calvo	3
+ PDF Chat	A Comparison of Two Shallow-Water Models with Nonconforming Adaptive Grids	2008	Amik St-Cyr Christiane Jablonowski John M. Dennis Henry M. Tufo Stephen Thomas	3
+	Optimal tuning of the hybrid Monte Carlo algorithm	2013	Alexandros Beskos Natesh S. Pillai Gareth O. Roberts J. M. Sanz‐Serna Andrew M. Stuart	3
+	Hybrid Monte Carlo on Hilbert spaces	2011	Alexandros Beskos F. J. Pinski J. M. Sanz‐Serna Andrew M. Stuart	3
+ PDF Chat	Evaluating Data Assimilation Algorithms	2012	Kody J. H. Law Andrew M. Stuart	3
+ PDF Chat	Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods	2011	Mark Girolami Ben Calderhead	3
+ PDF Chat	Stochastic Learning Approach for Binary Optimization: Application to Bayesian Optimal Design of Experiments	2022	Ahmed Attia Sven Leyffer Todd Munson	3
+ PDF Chat	Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs	2020	Karina Koval Alen Alexanderian Georg Stadler	3
+ PDF Chat	GRADIENT-BASED STOCHASTIC OPTIMIZATION METHODS IN BAYESIAN EXPERIMENTAL DESIGN	2014	Xun Huan Youssef Marzouk	3
+	On Bayesian A- and D-Optimal Experimental Designs in Infinite Dimensions	2015	Alen Alexanderian Philip Gloor Omar Ghattas	3
+	Markov Chain Monte Carlo and Numerical Differential Equations	2013	J. M. Sanz‐Serna	3
+ PDF Chat	Numerical Integrators for the Hybrid Monte Carlo Method	2014	Sergio Blanes Fernando Casas J. M. Sanz‐Serna	3
+ PDF Chat	Minimizing finite sums with the stochastic average gradient	2016	Mark Schmidt Nicolas Le Roux Francis Bach	2
+ PDF Chat	Nonlinear Goal-Oriented Bayesian Inference: Application to Carbon Capture and Storage	2014	Chad Lieberman Karen Willcox	2
+	Robust Stochastic Approximation Approach to Stochastic Programming	2009	Arkadi Nemirovski Anatoli Juditsky Guanghui Lan Alexander Shapiro	2
+ PDF Chat	Fast Bayesian experimental design: Laplace-based importance sampling for the expected information gain	2018	Joakim Beck Ben Mansour Dia Luis Espath Quan Long Raúl Tempone	2
+ PDF Chat	Cluster Sampling Filters for Non-Gaussian Data Assimilation	2018	Ahmed Attia Azam Moosavi Adrian Sandu	2
+ PDF Chat	Scalable and efficient algorithms for the propagation of uncertainty from data through inference to prediction for large-scale problems, with application to flow of the Antarctic ice sheet	2015	Tobin Isaac Noémi Petra Georg Stadler Omar Ghattas	2
+	Fast Incremental Method for Nonconvex Optimization	2016	Sashank J. Reddi Suvrit Sra Barnabás Póczos Alexander J. Smola	2
+ PDF Chat	A-optimal encoding weights for nonlinear inverse problems, with application to the Helmholtz inverse problem	2017	Benjamin Crestel Alen Alexanderian Georg Stadler Omar Ghattas	2
+	Asymptotic Theory for Solutions in Statistical Estimation and Stochastic Programming	1993	Alan J. King R. T. Rockafellar	2
+ PDF Chat	Inverse problems: A Bayesian perspective	2010	Andrew M. Stuart	2
+ PDF Chat	A local ensemble Kalman filter for atmospheric data assimilation	2004	Edward Ott Brian R. Hunt Istvan Szunyogh Aleksey V. Zimin Eric J. Kostelich M. Corazza Eugenia Kalnay D. J. Patil James A. Yorke	2
+	Asymptotic analysis of stochastic programs	1991	Alexander Shapiro	2
+	Efficiency improvement and variance reduction	1994	Pierre L’Ecuyer	2
+ PDF Chat	Fast ensemble smoothing	2007	Sai Ravela Dennis McLaughlin	2
+	Replica Monte Carlo Simulation of Spin-Glasses	1986	Robert H. Swendsen Jian‐Sheng Wang	2
+	A computational framework for infinite-dimensional Bayesian inverse problems. Part I: The linearized case, with application to global seismic inversion	2013	Tan Bui‐Thanh Omar Ghattas James L. Martin Georg Stadler	2
+ PDF Chat	Asymptotic Behavior of Statistical Estimators and of Optimal Solutions of Stochastic Optimization Problems	1988	Jitka Dupačová Roger J.‐B. Wets	2
+	A derivative-free trust region framework for variational data assimilation	2015	Elías D. Niño-Ruiz Adrian Sandu	2
+	Accelerated Monte Carlo for Optimal Estimation of Time Series	2005	Francis J. Alexander Gregory L. Eyink Juan M. Restrepo	2
+ PDF Chat	An optimization framework to improve 4D-Var data assimilation system performance	2014	Alexandru Cioaca Adrian Sandu	2
+	An alternating direction implicit method for solving the shallow water equations	1971	Bertil Gustafsson	2