Differentiable tree-based models for tabular data

The Julia implementation of the generalised hierarchical Gaussian filter

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

Lazy, structured, and efficient operations with kernel matrices.

An multi-platform spiking neural network simulator

Easily optimize generic performance metrics in differentiable learning.

General Relativistic Orbital Dynamics in Julia

GPT-3 as a generative function in Gen.

Memory efficient one-hot array encodings

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.

From Semiconductor to TransistorLevel Modeling in Julia

Simple, blazing fast, transformer components.

Representing machine learning models using mathematical programming

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

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

Uniform interface for machine learning in Julia

Scalable nonparametric clustering with unified marker gene selection for single-cell RNA-seq data

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An Open-Source End-to-End Pipeline for Spiral Magnetic Resonance Image (MRI) Reconstruction in Julia

A forward McCormick operator library

A neural network accelerated solver for mixed-strategy solutions of trajectory games. Do you even lift?

A pure Julia implementation of the Targeted Minimum Loss-based Estimation

Adversarial attacks for Neural Networks written with FluxML

SossMLJ makes it easy to build MLJ machines from user-defined models from the Soss probabilistic programming language

Differentiable JUlia ICE model

Julia package for microstructure imaging

Simple, blazing fast, message-passing graph neural network.

Measures (metrics) for statistics and machine learning

Train a spiking recurrent neural network

CUDA integration for the NNlib API

Modern Hopfield layer implementations in Julia

A differentiable parametrization of a group of unitary matrices.

Experimental features for Flux.jl

Protein ribbon plots implemented in Julia using Makie

Adaptive stress testing of black-box systems within POMDPs.jl

Implementation of Integral Probability Measures in Julia

Julia package with several functions to train and analyze Autoencoder-based neural networks

Graph-building for AtomicGraphNets

Sklearn Interface and Distributed Training for Flux.jl

Collection of layers that can perform arithmetic operations