2 citations · 3 across the 5 of their papers we have counts for
5 papers
Viability of Tensor Train Methods for Geophysical Fluid Dynamics
Jeremy Lilly, Derek DeSantis, Mark R. Petersen
Tensor train (TT) methods have recently gained popularity for accelerating the solving of systems of PDEs. Here, we evaluate the performance of TT methods in the context of geophys…
Breaking the Curse of Dimensionality: Solving Configurational Integrals for Crystalline Solids by Tensor Networks
Duc P. Truong, Benjamin Nebgen, Derek DeSantis +3
Accurately evaluating configurational integrals for dense solids remains a central and difficult challenge in the statistical mechanics of condensed systems. Here, we present a nov…
Space-Time Spectral Element Tensor Network Approach for Time Dependent Convection Diffusion Reaction Equation with Variable Coefficients
Dibyendu Adak, Duc P. Truong, Radoslav Vuchkov +5
In this paper, we present a new space-time Petrov-Galerkin-like method. This method utilizes a mixed formulation of Tensor Train (TT) and Quantized Tensor Train (QTT), designed for…
High-order Tensor-Train Finite Volume Method for Shallow Water Equations
Mustafa Engin Danis, Duc P. Truong, Derek DeSantis +3
In this paper, we introduce a high-order tensor-train (TT) finite volume method for the Shallow Water Equations (SWEs). We present the implementation of the order Upwind a…
Studying the Impact of Latent Representations in Implicit Neural Networks for Scientific Continuous Field Reconstruction
Wei Xu, Derek Freeman DeSantis, Xihaier Luo +5
Learning a continuous and reliable representation of physical fields from sparse sampling is challenging and it affects diverse scientific disciplines. In a recent work, we present…