A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.
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Updated
Mar 14, 2023
A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.
Official development repository for SUNDIALS - a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. Pull requests are welcome for bug fixes and minor changes.
Code for the paper "Learning Differential Equations that are Easy to Solve"
PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks
C++ library for ODE integration via Taylor's method and LLVM
开源Go语言数值算法库(An open numerical library purely based on Go programming language)
Self advection, external force and pressure solve to a velocity field represented by a MaC grid.
Probabilistic Numerical Differential Equation solvers via Bayesian filtering and smoothing
ODE integration using Taylor's method, and more, in Julia
A collection of numerical methods written in Nim
N body gravity attraction problem solver
Bulirsch-Stoer integration of systems of ordinary differential equations in JavaScript
Python wrapper of LSODA (solving ODEs) which can be called from within numba functions.
Configurable ODE/PDE solver
Python library for ODE integration via Taylor's method and LLVM
Numerical methods to solve ordinary differential equations in Rust.
Workshop materials for training in scientific computing and scientific machine learning
Work in Progress to refactor and modernize the ODEPACK Library
Owl's Differential Equation Solvers
An Introduction to Modeling Neuronal Dynamics - Borgers in python, Single Neuron Models, Mathematical Modeling, Computational Neuroscience, Hodgkin-Huxley Equations, Differential Equations, Brain Rhythms, Synchronization, Dynamics
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