Estimating Eigenvalues with neural Networks

Original article was published by /u/some_dadaism on Deep Learning

I am interested in inverting a matrix by estimating an Inverse with a neural network. This should potentially be faster for very large matrices than inverting them deterministically. Also it is probably cheap to check if the Inverse is good enough or if the error by the network is too big. Maybe the way to go is also to estimate Eigenvalues of the matrix. Can someone point me to a paper that works with that idea?

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