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A dynamically generated activity graph to show your GitHub activities of last 31 days.
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.
PositionBasedDynamics is a library for the physically-based simulation of rigid bodies, deformable solids and fluids.
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.
Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation
PyPSA: Python for Power System Analysis
Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).
The Operator Splitting QP Solver
An open-source Python framework for hybrid quantum-classical machine learning.
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. https://docs.kidger.site/diffrax/
[Deprecated] Use Cornerstone3D Instead https://cornerstonejs.org/
Fluid simulation engine for computer graphics applications
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
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 🙌
Physical Symbolic Optimization
automatic differentiation made easier for C++
SPlisHSPlasH is an open-source library for the physically-based simulation of fluids.
Creusot helps you prove your Rust code is correct.
Store files as YouTube videos == infinite disk space
A package for the sparse identification of nonlinear dynamical systems from data
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
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.