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Top 13 Eigenvalue Open-Source Projects
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Linear-Algebra-With-Python
Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.
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InfluxDB
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gosl
Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.
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Tiger
C++ Matrix -- High performance and accurate (e.g. edge cases) matrix math library with expression template arithmetic operators (by hosseinmoein)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
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russell
Rust Scientific Libary. Special functions (Bessel, Elliptic, Beta, Gamma, Erf). Linear algebra. Sparse solvers. ODE and DAE solvers. Probability distributions. Tensor calculus.
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eigenlearning
codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"
Project mention: Python for Econometrics for Practitioners [Free Online Courses] | /r/CompSocial | 2023-08-24Linear Algebra with Python: This training will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skill sets. Suitable for statisticians, econometricians, quantitative analysts, data scientists, etc. to quickly refresh linear algebra with the assistance of Python computation and visualization. Core concepts covered are: linear combination, vector space, linear transformation, eigenvalues and -vector, diagnolization, singular value decomposition, etc.
Project mention: Linus Torvalds adds arbitrary tabs to kernel code | news.ycombinator.com | 2024-04-17Indentation by steps of 3 spaces is common in old Fortran 77 code. This is LAPACK for example. Scroll down to about line 400 to see actual code, not comments.
https://github.com/Reference-LAPACK/lapack/blob/master/SRC/c...
For large and matrices you can use the (restarted) Arnoldi method to compute a partial Schur decomposition AQ=QR where Q is tall and skinny and R has a few dominant eigenvalues on the diagonal (i.e. eigenvalues on the boundary of the convex hull).
MATLAB uses ARPACK's implementation of this when you call `eigs`
I wrote my own implementation ArnoldiMethod.jl in julia, which unlike MATLAB/ARPACK supports arbitrary number types, and also should be more stable in general, and equally fast.
[1] https://github.com/JuliaLinearAlgebra/ArnoldiMethod.jl
Project mention: What numerical libraries (besides LAPACK) do you normally use in Fortran? | /r/fortran | 2023-06-09I have used many codes by John Burkardt https://people.sc.fsu.edu/~jburkardt/f_src/f_src.html and classified them at https://github.com/Beliavsky/Burkardt-Fortran-90 .
Eigenvalues related posts
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What Is a Schur Decomposition?
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Is Rust going to become a language for scientific computing and data analysis anytime soon?
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[R] Neural Tangent Kernel Eigenvalues Accurately Predict Generalization
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[R] Neural Tangent Kernel Eigenvalues Accurately Predict Generalization
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Beautiful pictures in algebra?
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eigenvalues of random matrices (bohemian eigenvalues)
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eigenvalues of random matrices (bohemian eigenvalues kinda)
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A note from our sponsor - InfluxDB
www.influxdata.com | 11 May 2024
Index
What are some of the best open-source Eigenvalue projects? This list will help you:
Project | Stars | |
---|---|---|
1 | eiten | 2,694 |
2 | Linear-Algebra-With-Python | 2,160 |
3 | gosl | 1,808 |
4 | lapack | 1,403 |
5 | vsl | 329 |
6 | Tiger | 107 |
7 | ArnoldiMethod.jl | 93 |
8 | sparse-linear-algebra | 87 |
9 | russell | 69 |
10 | eigenlearning | 49 |
11 | SLICOT-Reference | 40 |
12 | Burkardt-Fortran-90 | 39 |
13 | BohemianMatrices | 7 |
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