Graph-building for AtomicGraphNets

Sklearn Interface and Distributed Training for Flux.jl

Collection of layers that can perform arithmetic operations

A high-performance library for gradient based quantum optimal control

JutulDarcyRules: ChainRules extension to Jutul and JutulDarcy

Lightweight module of neural differential equations in Kinetic.jl

Operator layers for Flux.jl that allow for the construction of Neural Operator models by using Flux's API. Useful for discretization-independent spatio-temporal ML models.

Linear models

Differentiable 2d rasterizer in Julia

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A Julia package for parameterized convex approximators including parameterized log-sum-exp (PLSE) network.

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Neural-Network Outlier Detection Algorithms for Julia

DNA Motif discovery that includes the discovery of flexible (long or gapped) motifs.

Julia implementation of the Gumbel-Softmax reparametrization trick compatible with Zygote and ForwardDiff

A Julia based implementation of Plug and Play Language Models

Layerwise Relevance Propagation in Julia.

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Jet operator pack for seismic modeling dependent on WaveFD.jl. Part of the COFII framework.

Bayesian addition to Flux.jl

A Julia package for modelling Algorithmic Recourse Dynamics.

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A powerful, no code solution for control and systems engineering

Compressed belief-state MDPs in Julia compatible with POMDPs.jl

A Julia package for people that love to learn new things about constraints

Evidential Deep Learning Layers for Flux

Julia implementation of the ISOKANN algorithm for the computation of invariant subspaces of Koopman operators

Subspace Inference package for uncertainty analysis in deep neural networks and neural ordinary differential equations using Julia

A small Julia package to facilitate working with the Trillion Dollar Words dataset.

Lightweight module for fusing physical and neural models

Deep and convolutional neural networks with feedback operations in Flux.

Monotone Cubic B-Splines (arXiv:2307.01748)

Dynamical systems identification

Integrate deep neural network and reverse mode automatic differentiation into Gauss process, have fun !

Advanced process control for AutomationLabs

A collection of background subtraction algorithms for spectroscopic data

Non-critical functions for SeaPearl

Scalable and distributed matrix-free abstractions for machine learning and scientific computing

Computational models of algorithmic competition