Diagnostics for Oceananigans

Geothermal Cloud for Machine Learning

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

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

A Julia wrapper for the NVIDIA Collective Communications Library.

Data and functions to support Julia projects based on the book "Regression and Other Stories" by Andrew Gelman, Jennifer Hill and Aki Vehtari.

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.

Computing mixed-strategy Nash Equilibria for games involving multiple players

Flux reconstruction method for advection-diffusion type physics

A Modern Binary Ephemeris Reader for Julia, in Julia.

Julia package for general many-body exact diagonalization calculation.

Useful Layers for Knet

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Welcome to Peridynamic Laboratory (PeriLab), a powerful software solution designed for tackling Peridynamic problems.

SeaPearl's pool of examples

Parallel tools for ITensors.jl.

Differentiable tree-based models for tabular data

🎲 Parameter estimation for Oceananigans using EnsembleKalmanProcesses

A package to calibrate atmospheric turbulence and convection parameterizations using gradient-free ensemble Kalman methods

A tool for visualizing tensor network contractions.

MDToolbox.jl: A Julia package for molecular dynamics trajectories analysis and modeling of biomolecules

An multi-platform spiking neural network simulator

General Relativistic Orbital Dynamics in Julia

Simulation tools for Mixed Models

Probabilistic inference using contraction of tensor networks

Julia package for multicellular modeling

DynamicHMC versions of StatisticalRethinking models

A generic FEM solver by meta-expressions

Simulating Rydberg atom dynamics with Tensor Networks

A Julia wrapper for cusolverRF

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From Semiconductor to TransistorLevel Modeling in Julia

Simple, blazing fast, transformer components.

MeshGraphNets.jl is a software package for the Julia programming language that provides an implementation of the MeshGraphNets framework by Google DeepMind for simulating mesh-based physical systems via graph neural networks.

Useful tools for working with isometric or unitary tensors

WIP: Wrapper package for the sample method in Stan's cmdstan executable.

GPT-3 as a generative function in Gen.

Mixed complementarity problems parameterized by "runtime"-parameters with support for implicit differentiation.

Uniform interface for machine learning in Julia