Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Neural Network primitives with multiple backends

A Julia framework for invertible neural networks

Read ONNX graphs in Julia

Complex neural network examples for Flux.jl

Deep RNN, LSTM, GRU, GF-RNN, and GF-LSTMs in Julia

Restricted Boltzmann Machines in Julia

Visualization for Flux.Chain neural networks

Julia artificial 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.

Import/export ONNX models

Sum-product networks in Julia.

Generic artificial neural networks in Julia

A spiking neural network simulator written in Julia.

Hacking torch-like neural networks in Julia

A Julia wrapper for the Fast Artificial Neural Network Library (FANN)

RNN package for Julia

Move your models to Knet!

A simple feed-forward neural network for multi-label classification

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