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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.
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
Grid-based approximation of partial differential equations in Julia
Python package for solving partial differential equations using finite differences.
OSS library that implements deep learning methods for partial differential equations and much more
FeOs - A Framework for Equations of State and Classical Density Functional Theory
A Physics-Informed Neural Network to solve 2D steady-state heat equations.
Materials to support learning with my YouTube channel, https://www.youtube.com/c/EquitableEquations.
Turn papers, code, and docs into presentation-ready, natively editable PPTX in Codex / Claude Code. Native charts and equations, speaker notes, click-build animations, and an independent critic review before delivery.
Think with AI beyond the chat box. A shared canvas for handwriting, equations, diagrams, and spatial reasoning.