29 citations · 64 across the 9 of their papers we have counts for
4 papers · 1 filter
Goal-Oriented Low-Rank Tensor Decompositions for Numerical Simulation Data
Daniel M. Dunlavy, Eric T. Phipps, Hemanth Kolla +2
We introduce a new low-dimensional model of high-dimensional numerical simulation data based on low-rank tensor decompositions. Our new model aims to minimize differences between t…
Accurate Data-Driven Surrogates of Dynamical Systems for Forward Propagation of Uncertainty
Saibal De, Reese E. Jones, Hemanth Kolla
Stochastic collocation (SC) is a well-known non-intrusive method of constructing surrogate models for uncertainty quantification. In dynamical systems, SC is especially suited for…
Efficient Computation of Tucker Decomposition for Streaming Scientific Data Compression
Saibal De, Zitong Li, Hemanth Kolla +1
The Tucker decomposition, an extension of singular value decomposition for higher-order tensors, is a useful tool in analysis and compression of large-scale scientific data. While…
Randomized Functional Sparse Tucker Tensor for Compression and Fast Visualization of Scientific Data
Prashant Rai, Hemanth Kolla, Lewis Cannada +1
We propose a strategy to compress and store large volumes of scientific data represented on unstructured grids. Approaches utilizing tensor decompositions for data compression have…