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Tags: Science and math
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CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript

Apache Mahout - an environment for quickly creating scalable, performant machine learning applications.

  • apache-mahout
  • cuda
  • python
  • rust

Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and relative code.

PyPSA: Python for Power System Analysis

  • python
  • optimisation
  • energy-system
  • power-systems-analysis

The Classiq Library is the largest collection of quantum algorithms and applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌

  • quantum-algorithms
  • quantum-software
  • quantum-applications
  • quantum-open-source

automatic differentiation made easier for C++

  • automatic-differentiation
  • auto-differentiation
  • autodiff
  • autodifferentiation

Mixed-precision math, linear-algebra & retrieval kernels, 4000+ symbols from 4-bit numbers to 128-bit complex, for x86, Arm, RISC-V, LoongArch, Power & WASM, AMX & SME included 📐

Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.