226 citations · 733 across the 101 of their papers we have counts for
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Case study of SARS-CoV-2 transmission risk assessment in indoor environments using cloud computing resources
Kumar Saurabh, Santi Adavani, Kendrick Tan +5
Complex flow simulations are conventionally performed on HPC clusters. However, the limited availability of HPC resources and steep learning curve of executing on traditional super…
Feature engineering for microstructure-property mapping in organic photovoltaics
Sepideh Hashemi, Baskar Ganapathysubramanian, Stephen Casey +2
Linking the highly complex morphology of organic photovoltaic (OPV) thin films to their charge transport properties is critical for achieving high performance material system that…
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs
Biswajit Khara, Aditya Balu, Ameya Joshi +4
We consider a mesh-based approach for training a neural network to produce field predictions of solutions to parametric partial differential equations (PDEs). This approach contras…
Differentiable Spline Approximations
Minsu Cho, Aditya Balu, Ameya Joshi +6
The paradigm of differentiable programming has significantly enhanced the scope of machine learning via the judicious use of gradient-based optimization. However, standard differen…
Scalable adaptive PDE solvers in arbitrary domains
Kumar Saurabh, Masado Ishii, Milinda Fernando +6
Efficiently and accurately simulating partial differential equations (PDEs) in and around arbitrarily defined geometries, especially with high levels of adaptivity, has significant…
A projection-based, semi-implicit time-stepping approach for the Cahn-Hilliard Navier-Stokes equations on adaptive octree meshes
Makrand A. Khanwale, Kumar Saurabh, Masado Ishii +3
The Cahn-Hilliard Navier-Stokes (CHNS) system provides a computationally tractable model that can be used to effectively capture interfacial dynamics in two-phase fluid flows. In t…
Distributed Multigrid Neural Solvers on Megavoxel Domains
Aditya Balu, Sergio Botelho, Biswajit Khara +6
We consider the distributed training of large-scale neural networks that serve as PDE solvers producing full field outputs. We specifically consider neural solvers for the generali…