Parallel tools for ITensors.jl.

SeaPearl's pool of examples

Differentiable tree-based models for tabular data

A tool for visualizing tensor network contractions.

🎲 Parameter estimation for Oceananigans using EnsembleKalmanProcesses

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

Probabilistic inference using contraction of tensor networks

A Julia wrapper for cusolverRF

From Semiconductor to TransistorLevel Modeling in Julia

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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.

Simple, blazing fast, transformer components.

Julia package for multicellular modeling

DynamicHMC versions of StatisticalRethinking models

Useful tools for working with isometric or unitary tensors

A generic FEM solver by meta-expressions

Simulating Rydberg atom dynamics with Tensor Networks

Representing machine learning models using mathematical programming

An unofficial Julia wrapper for the RAPIDS.ai ecosystem using PythonCall.jl

Uniform interface for machine learning in Julia

Make turbulence with words

Integrating Neural Ordinary Differential Equations, the Method of Lines, and Graph Neural Networks

Plotting tools for Unfold.jl based on Makie.jl and AlgebraOfGraphics.jl

Julia implementation of ADMM solver on multiple GPUs

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Simple Julia Lattice Boltzmann Solver for Thin Liquid Films and Droplets, approximating the thin film equation.

Package to simulate the thermal evolution of magmatic systems

Package that provides a integrated Julia workflow for molecular dyanmics simulations.

MPS and MPO methods based on ITensor (ITensors.jl)

Macros to define custom adjoints for TensorOperations.jl

Propagate waves efficiently, optically, physically, differentiably with Julia Lang.

Modern Hopfield layer implementations in Julia

A new lightweight package for Deep Learning with Julia

🧊 Coupled and stand-alone simulations of sea ice for Earth system modeling

CUDA integration for the NNlib API

Reduced basis methods for parametrised eigenproblems

Train a spiking recurrent neural network

Implementation of Integral Probability Measures in Julia