AI · alternatives · 2026
24 alternatives to Implementing Truncated Matrix Decompositions for Core.Matrix
Eigendecompositions and Singular Value Decompositions appear in a variety of settings in machine learning and data mining. The eigendecomposition looks like so: $$ \mathbf{A}=\mathbf{Q}\mathbf{\Lambda}\mathbf{Q}^{-1} $$ $ \mathbf{Q} $ contains the eigen...
This project implements truncated matrix decomposition algorithms for Core.Matrix, a Clojure linear algebra library. It provides efficient eigendecomposition and singular value decomposition capabilities for machine… Below are 24 products that do a similar job, ranked by how close each is in meaning and then by launch-day votes. Implementing Truncated Matrix Decompositions for Core.Matrix launched in 2014; newer entries below may have overtaken it.
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Bitmap & tilemap generation from a single example with the help of ideas from quantum mechanics - mxgmn/WaveFunctionCollapse
2016 · github.com · its alternatives →
- 2

Algebraic enhancements for GEMM & AI accelerators. Contribute to trevorpogue/algebraic-nnhw development by creating an account on GitHub.
2024 · github.com · its alternatives →
- 3

Trying to do gradient descent using automatic differentiation over branchy programs? Or to combine them with neural networks for end-to-end training? Then this might be interesting to you. We develped DiscoGrad, a tool for automatic differentiation through C++ programs involving input-dependent control flow (e.g., "if (f(x) < c) { ... }", differentiating wrt. x) and randomness. Our initial motivation was to enable the use of gradient descent with simulations, which often rely heavily on such discrete branching. The latter makes plain autodiff mostly useless, since it can only account for the…
2024 · github.com · its alternatives →
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A Python library for detecting patterns and anomalies in massive datasets using the Matrix Profile - target/matrixprofile-ts
2019 · github.com · its alternatives →
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Long-simmering side project that is finally ready to see the light. HAMTs are a cool persistent data structure and implementing one has been a lot of fun. Beyond the code, there is likely some value in the extensive and largely complete implementation docs; basic benchmarks are linked in the README, too. Kind of aiming to be "the libavl for HAMTs". That is obviously a high and aspirational bar but a distinct possibility if it stirs up a little interest and/or contribution. Anyways, it's time for this to go out, collect feedback and maybe even some use outside of toy projects. Let me…
2023 · github.com · its alternatives →
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I built a Rust-powered Wavelet Matrix library for Python. There were surprisingly few practical Wavelet Matrix implementations available for Python, so I implemented one with a focus on performance, usability, and typed APIs. It supports fast rank/select, top-k, quantile, range queries, and even dynamic updates. Feedback welcome!
Dec 2025 · pypi.org · its alternatives →
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TurboQuant WASM SIMD vector compression — 3 bits/dim with fast dot product. Requires relaxed SIMD (Chrome 114+, Firefox 128+, Safari 18+, Node 20+) - teamchong/turboquant-wasm
Apr 2026 · github.com · its alternatives →
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Linear algebra concepts implemented in Go, mainly matrix manipulation - igomez10/linearalgebra
Jun 2026 · github.com · its alternatives →
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A simple re-implementation of Google's sparsehash as a learning excercise. - qpfiffer/Simple-Sparsehash
2015 · github.com · its alternatives →
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MatrixEase▲83A visualization and analysis tool for large matrix data
2022 · matrixease.com · its alternatives →
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R package to model Mixed Integer Linear Programs. Contribute to dirkschumacher/ompr development by creating an account on GitHub.
2017 · github.com · its alternatives →
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Contribute to seiflotfy/pcsa development by creating an account on GitHub.
2018 · github.com · its alternatives →
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It turns out the inverse of the Hessian of a deep net is easy to apply to a vector. Doing this naively takes cubically many operations in the number of layers (so impractical), but it's possible to do this in time linear in the number of layers (so very practical)! This is possible because the Hessian of a deep net has a matrix polynomial structure that factorizes nicely. The Hessian-inverse-product algorithm that takes advantage of this is similar to running backprop on a dual version of the deep net. It echoes an old idea of Pearlmutter's for computing Hessian-vector products. Maybe this…
Jan 2026 · github.com · its alternatives →
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2024 · gitlab.com · its alternatives →
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An Evaluation of Linear Probing Hashtable Algorithms - senderista/hashtable-benchmarks
2019 · github.com · its alternatives →
- 17

Fast equality saturation in Haskell
2022 · hackage.haskell.org · its alternatives →
- 18

Accelerated array computing and code transformations for R - r-xla/anvl
Mar 2026 · github.com · its alternatives →
- 19SP
https://github.com/tracyhenry/Kyrix Open source MIT project from Turing award winner Michael Stonebraker. Seeking contributors.
2020 · its alternatives →
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🧩 Shape-Safe Symbolic Differentiation with Algebraic Data Types - breandan/kotlingrad
2021 · github.com · its alternatives →
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Portable matrix multiplication library in C. Contribute to webDva/matrixmul development by creating an account on GitHub.
2018 · github.com · its alternatives →
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A NetworkX implementation of "Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters" (KDD 2017). - benedekrozemberczki/EgoSplitting
2020 · github.com · its alternatives →
- 23

C++ bindings for CBLAS (Basic Linear Algebra Subprograms). - nperf/nblas
2015 · github.com · its alternatives →
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A simplified version of the Wave Function Collapse algorithm - victorqribeiro/simpleWFC
2022 · github.com · its alternatives →
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Ranked by how close each launch is in meaning, then by votes. Prices were read from each product’s own site when checked and can change. Refine with your own description →