Optimal experimental design of ODE and DAE systems in julia

Linear models

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

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Ship maneuvering simulation tool with respect to ShipMMG model

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

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Neural-Network Outlier Detection Algorithms for Julia

Bayesian addition to Flux.jl

Unfortunately, FMUs (fmi-standard.org) are not differentiable by design. To enable their full potential inside Julia, FMISensitivity.jl makes FMUs fully differentiable, regarding to: states and derivatives | inputs, outputs and other observable variables | parameters | event indicators | explicit time | state change sensitivity by event

A Julia package for modelling Algorithmic Recourse Dynamics.

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Layerwise Relevance Propagation in Julia.

Package for fitting models according to the deep compartment modeling framework for pharmacometric applications.

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

A Julia based implementation of Plug and Play Language Models

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

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Evidential Deep Learning Layers for Flux

Bayesian Safety Signal Detection in Julia

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

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

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

A powerful, no code solution for control and systems engineering

Julia Package for Active Inference

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

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Advanced process control for AutomationLabs

Deep and convolutional neural networks with feedback operations in Flux.

A Julia package containing GNC algorithms for autonomous aerospace systems

Monotone Cubic B-Splines (arXiv:2307.01748)

Lightweight module for fusing physical and neural models

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

Power spectrum inference of irregularly sampled time series using Gaussian Processes in Julia

Dynamical systems identification

Differential Inequality Algorithms for Parametric ODEs

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

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