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#

ode

Here are 424 public repositories matching this topic...

Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.

  • UpdatedFeb 11, 2025
  • Julia

An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations

  • UpdatedMar 17, 2025
  • Julia

A collection of resources regarding the interplay between differential equations, deep learning, dynamical systems, control and numerical methods.

  • UpdatedSep 13, 2024

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

  • UpdatedMar 14, 2025
  • Julia
neurodiffeq

A library for solving differential equations using neural networks based on PyTorch, used by multiple research groups around the world, including at Harvard IACS.

  • UpdatedFeb 22, 2025
  • Python

High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)

  • UpdatedMar 16, 2025
  • Julia

Convert julia objects to LaTeX equations, arrays or other environments.

  • UpdatedFeb 5, 2025
  • Julia

Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization

  • UpdatedJan 23, 2025
  • Python

Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.

  • UpdatedMar 17, 2025
  • Julia

Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization

  • UpdatedFeb 14, 2025
  • Julia

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.

  • UpdatedMar 17, 2025
  • Julia

Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

  • UpdatedMar 14, 2025
  • MATLAB

PyDEns is a framework for solving Ordinary and Partial Differential Equations (ODEs & PDEs) using neural networks

  • UpdatedFeb 9, 2024
  • Jupyter Notebook

GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem

  • UpdatedFeb 22, 2025
  • Julia

Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem

  • UpdatedFeb 17, 2025
  • Julia
easy-neural-ode

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