Run reduced-order battery, thermal, converter and BESS control models with transparent equations and repeatable testing.
JavaScript/TypeScript animation engine
Collection of notebooks about quantitative finance, with interactive python code.
Symbolic Learning in Python and Julia
Learning in infinite dimension with neural operators.
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.
Think with AI beyond the chat box. A shared canvas for handwriting, equations, diagrams, and spatial reasoning.
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
LAPACK development repository
Linear algebra, eigenvalues, FFT, Bessel, elliptic, orthogonal polys, geometry, NURBS, numerical quadrature, 3D transfinite interpolation, random numbers, Mersenne twister, probability distributions, optimisation, differential equations.
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
Brian is a free, open source simulator for spiking neural networks.
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
Next generation FEniCS problem solving environment for solving finite element problems
Python library for arbitrary-precision floating-point arithmetic
an extensive Qt5 & Qt6 Plotter framework (including a feature-richt plotter widget, a speed-optimized, but limited variant and a LaTeX equation renderer!), written fully in C/C++ and without external dependencies
FreeFEM source code
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Grid-based approximation of partial differential equations in Julia
The Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
Open-source cross-platform symbolic algebra library for C# and F#. Can be used for both production and research purposes.
Distributed High-Performance Symbolic Regression in Julia
Physics-Informed Neural networks for Advanced modeling
MACS -- Model-based Analysis of ChIP-Seq
Trixi.jl: Adaptive high-order numerical simulations of conservation laws in Julia
Fast C++ and Python library for state-vector simulation of quantum circuits.
Official development repository for SUNDIALS - a SUite of Nonlinear and DIfferential/ALgebraic equation Solvers. Pull requests are welcome for bug fixes and minor changes.
High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.
Markdown rendering + Latex extras (equations, tables, ...), with conversion features, for the scientific community
Firedrake is an automated system for the portable solution of partial differential equations using the finite element method (FEM)
FiPy is a Finite Volume PDE solver written in Python
Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
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.
Netgen/NGSolve is a high performance multiphysics finite element software. It is widely used to analyze models from solid mechanics, fluid dynamics and electromagnetics. Due to its flexible Python interface new physical equations and solution algorithms can be implemented easily.
A Control Systems Toolbox for Julia
Julia package for function approximation
a symbolic math expression evaluator for javascript
Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software.
an R package for structural equation modeling and more
A Codex Skill for converting Beamer PDFs into editable PowerPoint decks with native equations.
Translate arXiv papers and LaTeX projects with your own LLM API, preserving equations, citations, and document structure. Generate translated PDFs and editable source through a local app or batch CLI.
Exact chemical equation balancing with rational linear algebra.
Best Open-Source Linear Equation Solver Trainer 2026
Master Linear Equations Instantly: The 2026 Interactive Algebra Trainer
Local-first reading workspace for technical papers β select an equation, figure, or passage and get grounded, step-by-step walkthroughs (with tensor-shape tracing for ML).
Differentiable ensemble solvers for differential equations on GPUs, in JAX
CΓ©line (Circuit Emulation Layer for Integrated Nonlinear Equation Solving) is an audio plugin for building and emulating circuits in real time. This tool is aimed at musicians who want to emulate analog hardware, and keeps the experimentation safe and portable.
Markdown to Notion Converter β Paste, upload, or drag & drop Markdown and get clean, Notion API-compatible Block JSON instantly β with nested lists, checklists, tables, callouts, code blocks, toggles, and equations. Nothing ever leaves your browser. Free on ToolAdda.online.
Scientific Calculator β Use Scientific Calculator free on ToolAdda β quick, accurate, and browser-based. Free on ToolAdda.online.