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Artificial brains could point the way to ultra-efficient supercomputers
Sandia National Labs cajole Intel's neurochips into solving partial differential equations New research from Sandia National ...
An iterative method based on Picard's approach to ODEs' initial-value problems is proposed to solve first-order quasilinear PDEs with matrix-valued unknowns, in particular, the recently discovered ...
A new technical paper titled “Solving sparse finite element problems on neuromorphic hardware” was published by researchers ...
ABSTRACT: This article is devoted to developing a deep learning method for the numerical solution of the partial differential equations (PDEs). Graph kernel neural networks (GKNN) approach to ...
If you are interested in one of the opportunities below, please reach out directly to the faculty member listed below each project. Interested students can be either graduate students or upper-class ...
Lindsey Ellefson is Lifehacker’s Features Editor. She currently covers study and productivity hacks, as well as household and digital decluttering, and oversees the freelancers on the sex and ...
Prerequisites: This course covers advanced techniques for discretizing and solving PDEs. Some familiarity with ordinary differential equations, partial differential equations, Fourier transforms, ...
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