High Quality Geophysical Analysis provides a general purpose Bayesian and deterministic inversion framework for various geophysical methods and spatially distributed / timeseries data

Building and using pyramids for large raster data

Preheat your MCMC

ClimaAtmos.jl is a library for building atmospheric circulation models that is designed from the outset to leverage data assimilation and machine learning tools. We welcome contributions!

Distributed High-Performance Symbolic Regression in Julia

Paquete de equilibrio liquido/vapor

Kite and tether models for the simulation of kite power systems

Basic functionality for EarthSciML system

Models of gas-phase atmospheric chemistry and related processes

A Julia/JuMP Package for Power Network Optimization

-

Integrated Transmission and Distribution Optimization

A CPU- and GPU-friendly package for solving ordinary differential equations

A PowerModels Extension for Optimization of Power Network Restoration

Fast 1D LTE stellar spectral synthesis

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.

Award winning software library for nonlinear dynamics and nonlinear timeseries analysis

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

EDS spectrum analysis tools within the NeXL toolset

Julia package to run Dynamic Power System simulations. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

Quantum dynamics simulation environment

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

Julia for optimization simulation and modeling of PowerSystems. Part of the Scalable Integrated Infrastructure Planning Initiative at the National Renewable Energy Lab.

A full stack simulator of quantum hardware, from the low-level analog physics to high-level network dynamics. Includes discrete event simulator, symbolic representation for quantum object, and works with many backend simulators.

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

Controllers for airborne wind energy systems

Julia package for fitting regularized linear mixed-effect models on high-dimensional omics data.

Solve non-linear HJB equations.

Phylogenetic Estimation of Shifts in the Tempo of Origination

Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)

Tools for chemometrics and machine learning on high-dimensional data (e.g. Partial least squares regression/discrimination)

Julia library for fitting and analyzing state space models. Provides efficient implementations of various SSMs including the canonical Gaussian LDS (Kalman Filter/Smoother), Poisson LDS, HMMs, etc.

Trixi.jl: Adaptive high-order numerical simulations of conservation laws in Julia

Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia

ADRIA: Adaptive Dynamic Reef Intervention Algorithms. A multi-criteria decision support platform for informing reef restoration and adaptation interventions.

Julia implementation of the ISOKANN algorithm for the computation of invariant subspaces of Koopman operators

Julia package for simulating Dynamics on Networks

FMIBase.jl provides the foundation for the Julia packages FMIImport.jl and FMIExport.jl.

Atomic graph models for molecules and crystals in Julia

A standard library of components to model the world and beyond