Implementation of the Deep Q-learning algorithm to solve MDPs

Bayesian Generalized Linear models using `@formula` syntax.

A Julia package for Deep Backwards Stochastic Differential Equation (Deep BSDE) and Feynman-Kac methods to solve high-dimensional PDEs without the curse of dimensionality

Global glacier model using Universal Differential Equations for climate-glacier interactions

Turing + Makie = Turkie

Hyperparameter optimization algorithms for use in the MLJ machine learning framework

Transformations to contrained variables from ℝⁿ.

Multistart optimization methods in Julia.

Visualization for Flux.Chain neural networks

Atomic graph models for molecules and crystals in Julia

Use Optim to train Flux models and visualize loss landscapes

Implementation of advanced Sequential Monte Carlo and particle MCMC algorithms

Data-parallelism on CUDA using Transducers.jl and for loops (FLoops.jl)

Distributed Data Parallel Training of Deep Neural Networks

FMIFlux.jl is a free-to-use software library for the Julia programming language, which offers the ability to place FMUs (fmi-standard.org) everywhere inside of your ML topologies and still keep the resulting model trainable with a standard (or custom) FluxML training process.

Robust, Fast, and Parallel Global Sensitivity Analysis (GSA) in Julia

A foolproof way of doing ML with GUI elements.

Finds relationships between the parameters of a mathematical model

A Julia package for robust neural networks.

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

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Generate Julia package skeletons using a simple template system

Julia bindings for onnxruntime

Machine learning with Mill.jl for JSON documents

Write tabular data from Julia in LaTeX format.

Import/export ONNX models

Julia library for deep reinforcement learning

No need to train, he's a smooth operator

I heard you like compile times

Embedded finite element methods in Julia

Gmsh generated meshes for Gridap

Integrating diagramming and data visualization

Evolve Flux networks from scratch!

Implementations of single and multi-ellipsoid nested sampling

Interface package for featurizing atomic structures

Life Actuarial Maths

A common framework for implementing and using log densities for inference.

Common functions in actuarial and financial routines

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

Examples for Bayesian inference using DynamicHMC.jl and related packages.