Fast operator-overloading Jacobian & Hessian sparsity detection.

Differential equation problem specifications and scientific machine learning for common financial models

Accelerate your ML research using pre-built Deep Learning Models with Lux

Stochastic delay differential equations (SDDE) solvers for the SciML scientific machine learning ecosystem

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ClimaCoupler: bringing atmosphere, land, and ocean together

Deep Learning made easy and fast

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Tools for the Simulation and Execution of Quantum Annealing Algorithms

Geothermal Cloud for Machine Learning

An easy to use Flux implementation of the Kolmogorov Arnold Network. This is a Julia version of TorchKAN.

Simulate quantum systems consisting of many spins interacting via dipole-dipole interaction

A Julia wrapper for the NVIDIA Collective Communications Library.

Diagnostics for Oceananigans

Builds conductance based neural networks iteratively, from ion channels and synapses

Three Dimensional Magnetohydrodynamic(MHD) pseudospectral solvers written in julia with FourierFlows.jl

Benchmark tools for solvers

Julia MathML parser

Signal logging and scoping for DifferentialEquations.jl simulations.

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A tool to solve optimal control problem

Implicit Runge-Kutta Gauss-Legendre 16th order (Julia)

Implementation of SDDP (Stochastic Dual Dynamic Programming) using the StructJuMP modeling interface

Abstraction layer for spanning factor graphs over various technologies

DINCAE (Data-Interpolating Convolutional Auto-Encoder) is a neural network to reconstruct missing data in satellite observations.

Constrained and NoNlinear Optimizer of Least Squares

One stop solutions for all things optimization

Mixed-Integer Convex Programming: Branch-and-bound with Frank-Wolfe-based convex relaxations

An energy system optimization model that is flexible, computationally efficient, and academically robust.

Flux reconstruction method for advection-diffusion type physics

Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia

Symbolic-Numeric Universal Differential Equations for Automating Scientific Machine Learning (SciML)

Julia package for general many-body exact diagonalization calculation.

Simple differential equation solvers in native Julia for scientific machine learning (SciML)

Wrappers for the SciPy differential equation solvers for the SciML Scientific Machine Learning organization

Turbulence-resolving simulations of boundary-layer flows (DNS & LES)

Differentiable tree-based models for tabular data

Finite Element Module for Julia that focusses on gradient-robust discretisations and multiphysics problems

Useful Layers for Knet

Throw stuff