An analytical differential equation solver using genetic programming
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Updated
Feb 3, 2018 - Julia
An analytical differential equation solver using genetic programming
A numerical continuation code written in Julia based on Continuation Core (CoCo) by Dankowicz and Schilder
Binary library builder for Sundials for the SciML scientific machine learning open source software organization
数値計算100本ノック
Backend for DiffEqOnline, a webapp for scientific machine learning (SciML)
Library for simple upwind finite differences
A wrapper for the Python PyDSTool library for the SciML Scientific Machine Learning organization
Using TensorFlow for physics-informed neural networks for scientific machine learning (SciML)
Wrappers for arrays to make broadcasted operations multithreaded and multiprocessed for high-performance scientific machine learning (SciML)
A helper repository for diffeqpy to enable high-performance differential equation solving scientific machine learning (SciML) in Python
Storage of some simple implementations just for learning
Interface between the Systems Biology Markup Language and Julia
Automatic GPU, TPU, FPGA, Xeon Phi, Multithreaded, Distributed, etc. offloading for scientific machine learning (SciML) and differential equations
Automatic detection of sparsity in pure Julia functions for sparsity-enabled scientific machine learning (SciML)
Solve the Laplace-Beltrami equation in arbitrary coordinates, based on FastSphericalHarmonics.jl
I upload my numerical mathematics II homework here. It's all numerical methods for PDE.
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