Stars
An intuitive modeling interface for infinite-dimensional optimization problems.
Tools for easily handling objects like arrays of arrays and deeper nestings in scientific machine learning (SciML) and other applications
Readily pin Julia threads to CPU-threads
A modern, high-performance and comprehensive set of tools for transformations between any standard and user-defined reference frame.
Types with default field values, keyword constructors and (un-)pack macros
Efficient Astronomical Time transformations in Julia.
A Modern Binary Ephemeris Reader for Julia, in Julia.
A python-based end-to-end testing package that will be able to test orbit prediction accuracy for Open Source Orbit Integrators
Predictive Uncertainty Quantification through Conformal Prediction for Machine Learning models trained in MLJ.
An open-source community LSST Solar System Simulator
Compiles Julia code to a standalone library (experimental)
Transformations for the SatelliteToolbox.jl ecosystem.
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
Makes Julia reason with equations. General purpose metaprogramming, symbolic computation and algebraic equational reasoning library for the Julia programming language: E-Graphs & equality saturatio…
Code accompanying my blog post: So, what is a physics-informed neural network?
Read, write, and interact with data in the Digital RF and Digital Metadata formats
SMILI: Sparse Modeling Imaging Library for Interferometry
SciMLOperators.jl: Matrix-Free Operators for the SciML Scientific Machine Learning Common Interface in Julia
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
5AA1High-performance and differentiation-enabled nonlinear solvers (Newton methods), bracketed rootfinding (bisection, Falsi), with sparsity and Newton-Krylov support.
Data driven modeling and automated discovery of dynamical systems for the SciML Scientific Machine Learning organization
Symbolic programming for the next generation of numerical software