34 citations · 82 across the 15 of their papers we have counts for
4 papers · 1 filter
An efficient epistemic uncertainty quantification algorithm for a class of stochastic models: A post-processing and domain decomposition framework
Mahadevan Ganesh, Stuart C Hawkins, Alexandre Tartakovsky +1
Partial differential equations (PDEs) are fundamental for theoretically describing numerous physical processes that are based on some input fields in spatial configurations. Unders…
Physics-Informed Gaussian Process Regression for Probabilistic States Estimation and Forecasting in Power Grids
Tong Ma, David Alonso Barajas-Solano, Ramakrishna Tipireddy +1
Real-time state estimation and forecasting is critical for efficient operation of power grids. In this paper, a physics-informed Gaussian process regression (PhI-GPR) method is pre…
Bayesian phase estimation with adaptive grid refinement
Ramakrishna Tipireddy, Nathan Wiebe
We introduce a novel Bayesian phase estimation technique based on adaptive grid refinement method. This method automatically chooses the number particles needed for accurate phase…
FPDetect: Efficient Reasoning About Stencil Programs Using Selective Direct Evaluation
Arnab Das, Sriram Krishnamoorthy, Ian Briggs +2
We present FPDetect, a low overhead approach for detecting logical errors and soft errors affecting stencil computations without generating false positives. We develop an offline a…