A foolproof way of doing ML with GUI elements.

A Julia package for robust neural networks.

Generic UNet implementation written in pure Julia, based on Flux.jl

Machine learning with Mill.jl for JSON documents

No need to train, he's a smooth operator

Julia library for deep reinforcement learning

Import/export ONNX models

I heard you like compile times

Interface package for featurizing atomic structures

Evolve Flux networks from scratch!

Effortless Bayesian Deep Learning through Laplace Approximation for Flux.jl neural networks.

Clima's Land Model

TreeParzen.jl, a pure Julia hyperparameter optimiser with MLJ integration

An interface for accelerated simulation of high-dimensional collisionless and electrostatic plasmas.

A Julia implementation of sparse Gaussian processes via path-wise doubly stochastic variational inference.

Julia Toolkit with fairness metrics and bias mitigation algorithms

A time domain electrical energy grid modeling and simulation tool with a focus on the control of power electronics converters

Generative Models with trainable conditional distributions in Julia!

A Julia package for interacting with the Hugging Face dataset repository.

Interpretable Machine Learning via Rule Extraction

A turbulence-convection single column model cloud parameterization.

Neural Network based models for Natural Language Processing

A Julia toolbox with resampling methods to correct for class imbalance.

Learning state-space targets in dynamical systems

Pruning framework and methods for Flux

Neural network training, fast and easy.

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

Your local Flux surgeon

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

Package for Bayesian and classical estimation and inference based on statistics that are filtered through a trained neural net

Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia

Differentiable tree-based models for tabular data

SeaPearl's pool of examples

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

Easily optimize generic performance metrics in differentiable learning.

Lazy, structured, and efficient operations with kernel matrices.

Simple, blazing fast, transformer components.

From Semiconductor to TransistorLevel Modeling in Julia

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

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