1 citations · 1 across the 7 of their papers we have counts for
8 papers
High-Performance Star-M SVD for Big Data Compression
Md Taufique Hussain, Grey Ballard, Aditya Devarakonda +3
In the era of big data, effectively compressing large datasets while performing complex mathematical operations is crucial. Tensor-based decomposition methods have shown superior c…
Towards exascale fully relativistic pseudopotential density functional theory calculations enabled by mixed-precision computation and compressed-communication using residual based subspace iteration
Nikhil Kodali, Gourab Panigrahi, Nishant Gupta +6
Materials exhibiting noncollinear magnetism or strong spin-orbit-coupling underpin many spintronic and topological applications, but their simulations require complex two-component…
Rate-Distortion Bounds for Heterogeneous Random Fields on Finite Lattices
Sujata Sinha, Vishwas Rao, Robert Underwood +4
Since Shannon's foundational work, rate-distortion theory has defined the fundamental limits of lossy compression. Classical results, derived for memoryless and stationary ergodic…
Parametric Hierarchical Matrix Approximations to Kernel Matrices
Abraham Khan, Chao Chen, Vishwas Rao +1
Kernel matrices are ubiquitous in computational mathematics, often arising from applications in machine learning and scientific computing. In two or three spatial or feature dimens…
Structured Column Subset Selection for Bayesian Optimal Experimental Design
Hugo Díaz, Arvind K. Saibaba, Srinivas Eswar +2
We consider optimal experimental design (OED) for Bayesian inverse problems, where the experimental design variables have a certain multiway structure. Given different experime…
Optimal sensor placement under model uncertainty in the weak-constraint 4D-Var framework
Alen Alexanderian, Hugo Díaz, Vishwas Rao +1
In data assimilation, the model may be subject to uncertainties and errors. The weak-constraint data assimilation framework enables incorporating model uncertainty in the dynamics…
Bayesian D-Optimal Experimental Designs via Column Subset Selection
Srinivas Eswar, Vishwas Rao, Arvind K. Saibaba
This paper tackles optimal sensor placement for Bayesian linear inverse problems, a popular version of the more general Optimal Experimental Design (OED) problem, using the D-optim…
Randomized Preconditioned Solvers for Strong Constraint 4D-Var Data Assimilation
Amit N. Subrahmanya, Vishwas Rao, Arvind K. Saibaba
The Strong Constraint 4D Variational (SC-4DVAR) data assimilation method is widely used in climate and weather applications. SC-4DVAR involves solving a minimization problem to com…