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

Adversarial attacks for Neural Networks written with FluxML

Package that provides a integrated Julia workflow for molecular dyanmics simulations.

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

Differentiable JUlia ICE model

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

A simulation engine for models related to plants

Julia package for microstructure imaging

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Modern Hopfield layer implementations in Julia

A differentiable parametrization of a group of unitary matrices.

Measures (metrics) for statistics and machine learning

Experimental features for Flux.jl

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

Implementation of Integral Probability Measures in Julia

Discrete choice/random utility models in Julia

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

ADRIA: Adaptive Dynamic Reef Intervention Algorithms. A multi-criteria decision support platform for informing reef restoration and adaptation interventions.

Automorphism groups for CSets - generalizing the nauty algorithm to a broad class of data structures

Collection of layers that can perform arithmetic operations

Sklearn Interface and Distributed Training for Flux.jl

Graph-building for AtomicGraphNets

JutulDarcyRules: ChainRules extension to Jutul and JutulDarcy

Lightweight module of neural differential equations in Kinetic.jl

A high-performance library for gradient based quantum optimal control

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.

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Linear models

Differentiable 2d rasterizer in Julia

Useful sparse codes

A package for wrapping iterative MLJ models in a control strategy

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Approximate Bayesian Computation (ABC) with differential evolution (de) moves and model evidence (Z) estimates.

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

Reinforcement learning, compositionally

MLJ.jl interface for JLBoost.jl

MLJ.jl interface for JLBoost.jl

Regulatory networks

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