Great news!! A fast, butterfly (aka FFT-like), implementation of the Noiselet Transform [1] is now integrated into the LazyLinop toolbox [2] – “a python toolbox to ease and accelerate computations with (“matrix-free”) linear operators.” Thank you to Pascal Carrivain and Rémi Gribonval from the OCKHAM/INRIA team [3], in ENS Lyon, France (where I’m currently invited for a sabbatical year in 25-26) for this implementation. The idea came from common discussions we had together (I share my office with Pascal at ENS Lyon) about possible additional butterfly transformations to complete the (already long) list of operators integrated to LazyLinop. The whole Noiselet Tansform (and its inverse) is described here in the LazyLinop documentation, with a demonstration code in python. Enjoy!

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[1] https://laurentjacques.gitlab.io/post/some-comments-on-noiselets/

[2] https://faustgrp.gitlabpages.inria.fr/lazylinop/index.html "Lazylinop is a python toolbox to ease and accelerate computations with (“matrix-free”) linear operators. It provides glue to combine linear operators as easily as NumPy arrays, PyTorch/CuPy compatibility, standard signal/image processing linear operators, as well as advanced tools to approximate large matrices by efficient butterfly operators."

[3] https://team.inria.fr/ockham/

#Noiselet #CompressiveSensing #Butterfly #fft #InverseProblem #Python #Numeric #PyTorch

Inverse Parentheses

https://kellett.im/a/inverse-parentheses

#HackerNews #InverseParentheses #InverseProblem #CodingChallenge #HackerNews #TechTrends #Programming

New publication https://doi.org/10.1103/PhysRevB.111.205143

New algorithm for the #inverseproblem of Kohn-Sham #densityfunctionaltheory (#dft), i.e. to find the #potential from the #density.

Outcome of a fun collaboration of @herbst with the group of Andre Laestadius at #oslomet to derive first mathematical error bounds for this problem

#condensedmatter #planewave #numericalanalysis #convexanalysis #dftk