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ORCIDVishwas Rao
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2020 – today
- 2024
[c10]Sungho Shin, Vishwas Rao, Michel Schanen, Daniel Adrian Maldonado, Mihai Anitescu:
Scalable Multi-Period AC Optimal Power Flow Utilizing GPUs with High Memory Capacities. OSMSES 2024: 1-6- [i10]Amit N. Subrahmanya, Vishwas Rao, Arvind K. Saibaba:
Randomized Preconditioned Solvers for Strong Constraint 4D-Var Data Assimilation. CoRR abs/2401.15758 (2024) - [i9]Srinivas Eswar
, Vishwas Rao, Arvind K. Saibaba:
Bayesian D-Optimal Experimental Designs via Column Subset Selection: The Power of Reweighted Sensors. CoRR abs/2402.16000 (2024) - 2023
- [j11]S. Ashwin Renganathan, Vishwas Rao, Ionel Michael Navon:
CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis. J. Comput. Phys. 472: 111698 (2023) - 2022
- [j10]Vishwas Rao, Charlotte A. L. Haley, Mihai Anitescu:
LaplaceInterpolation.jl: A Julia package for fast interpolation on a grid. J. Open Source Softw. 7(69): 3766 (2022) - [j9]Shanyin Tong, Anirudh Subramanyam, Vishwas Rao:
Optimization under Rare Chance Constraints. SIAM J. Optim. 32(2): 930-958 (2022) - [c9]Vishwas Rao, Anirudh Subramanyam, Michel Schanen, Youngdae Kim, Ignas Satkauskas, Mihai Anitescu:
Frequency Recovery in Power Grids using High-Performance Computing. ICPP Workshops 2022: 20:1-20:6 - [i8]S. Ashwin Renganathan, Vishwas Rao, Ionel Michael Navon:
CAMERA: A Method for Cost-aware, Adaptive, Multifidelity, Efficient Reliability Analysis. CoRR abs/2203.01436 (2022) - [i7]Tyler E. Maltba, Vishwas Rao, Daniel Adrian Maldonado:
Learning the Evolution of Correlated Stochastic Power System Dynamics. CoRR abs/2207.13310 (2022) - 2021
- [j8]Azam S. Zavar Moosavi, Vishwas Rao, Adrian Sandu:
Machine learning based algorithms for uncertainty quantification in numerical weather prediction models. J. Comput. Sci. 50: 101295 (2021) - [j7]Vishwas Rao, Mihai Anitescu:
Efficient Computation of Extreme Excursion Probabilities for Dynamical Systems through Rice's Formula. SIAM/ASA J. Uncertain. Quantification 9(2): 731-762 (2021) - [c8]Varuni Katti Sastry, Romit Maulik, Vishwas Rao, Bethany Lusch, S. Ashwin Renganathan, Rao Kotamarthi:
Data-Driven Deep Learning Emulators for Geophysical Forecasting. ICCS (5) 2021: 433-446 - 2020
- [c7]Vishwas Rao, Romit Maulik, Emil M. Constantinescu, Mihai Anitescu:
A Machine-Learning-Based Importance Sampling Method to Compute Rare Event Probabilities. ICCS (6) 2020: 169-182 - [i6]Vishwas Rao, Mihai Anitescu:
Efficient computation of extreme excursion probabilities for dynamical systems. CoRR abs/2001.11904 (2020)
2010 – 2019
- 2019
- [j6]Nick Alger, Vishwas Rao, Aaron Myers, Tan Bui-Thanh, Omar Ghattas:
Scalable Matrix-Free Adaptive Product-Convolution Approximation for Locally Translation-Invariant Operators. SIAM J. Sci. Comput. 41(4): A2296-A2328 (2019) - [c6]Azam S. Zavar Moosavi, Vishwas Rao, Adrian Sandu:
A Learning-Based Approach for Uncertainty Analysis in Numerical Weather Prediction Models. ICCS (4) 2019: 126-140 - [i5]Romit Maulik, Vishwas Rao, Sandeep Madireddy, Bethany Lusch, Prasanna Balaprakash:
Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models. CoRR abs/1909.09144 (2019) - 2018
- [i4]Azam S. Zavar Moosavi, Vishwas Rao, Adrian Sandu:
A Learning Based Approach for Uncertainty Analysis in Numerical Weather Prediction Models. CoRR abs/1802.08055 (2018) - 2017
- [j5]Vishwas Rao, Adrian Sandu, Michael Ng, Elias David Niño Ruiz:
Robust Data Assimilation Using L1 and Huber Norms. SIAM J. Sci. Comput. 39(3) (2017) - 2016
- [j4]Vishwas Rao, Adrian Sandu:
A time-parallel approach to strong-constraint four-dimensional variational data assimilation. J. Comput. Phys. 313: 583-593 (2016) - 2015
- [j3]Vishwas Rao, Adrian Sandu:
A Posteriori Error Estimates for the Solution of Variational Inverse Problems. SIAM/ASA J. Uncertain. Quantification 3(1): 737-761 (2015) - [c5]Vishwas Rao, Adrian Sandu:
Parallel Solution of DDDAS Variational Inference Problems. ICCS 2015: 2474-2482 - [i3]Vishwas Rao, Adrian Sandu:
A Time-parallel Approach to Strong-constraint Four-dimensional Variational Data Assimilation. CoRR abs/1505.04515 (2015) - [i2]Ahmed Attia, Vishwas Rao, Adrian Sandu:
A Hybrid Monte-Carlo Sampling Smoother for Four Dimensional Data Assimilation. CoRR abs/1505.04724 (2015) - [i1]Vishwas Rao, Adrian Sandu, Michael Ng, Elias David Niño Ruiz:
Robust data assimilation using L1 and Huber norms. CoRR abs/1511.01593 (2015) - 2014
- [j2]Vishwas Rao, Rick Archibald, Katherine J. Evans:
Emulation to simulate low-resolution atmospheric data. Int. J. Comput. Math. 91(4): 770-780 (2014) - [j1]Vishwas Rao, Adrian Sandu:
An adjoint-based scalable algorithm for time-parallel integration. J. Comput. Sci. 5(2): 76-84 (2014) - [c4]Ahmed Attia, Vishwas Rao, Adrian Sandu:
A Sampling Approach for Four Dimensional Data Assimilation. DyDESS 2014: 215-226 - [c3]Vishwas Rao, Adrian Sandu:
A Posteriori Error Estimates for DDDAS Inference Problems. ICCS 2014: 1256-1265 - 2013
- [c2]Adrian Sandu, Alexandru Cioaca, Vishwas Rao:
Dynamic Sensor Network Configuration in InfoSymbiotic Systems Using Model Singular Vectors. ICCS 2013: 1909-1918 - 2012
- [c1]Vishwas Rao, Adrian Sandu:
An Adjoint Based Implementation of the Parareal Algorithm. ICCS 2012: 1021-1029
Coauthor Index
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