Trust-region methods with partitioned quasi-Newton approximations

A Julia package for building production-ready measures (metrics) for statistics and machine learning

A decision-making framework for the cost-efficient design of experiments, balancing the value of acquired experimental evidence and incurred costs.

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

A Julia package for real-time audification of ODEs and SDEs

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GraphNetCore.jl is a software package for the Julia programming language that provides an the core functionality of the MeshGraphNets.jl package. Some parts are based on the implementation of the MeshGraphNets framework by Google DeepMind for simulating mesh-based physical systems via graph neural networks.

Backend for Lux.jl

Neural-Network Outlier Detection Algorithms for Julia

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Layerwise Relevance Propagation in Julia.

A Julia based implementation of Plug and Play Language Models

Bayesian addition to Flux.jl

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

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

Independent Hypothesis Weighting for multiple testing with side-information in Julia

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

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A Julia package for modelling Algorithmic Recourse Dynamics.

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

Optimally tuned ridge regression when features can be partitioned into groups.

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

Julia Package for Active Inference

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

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

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

A package with exported learning networks that combine resampling methods from Imbalance.jl and classification models from MLJ

Bayesian Safety Signal Detection in Julia

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

This repo is for the final project for Comp541 Deep Learning class in Koc University.

A powerful, no code solution for control and systems engineering

Evidential Deep Learning Layers for Flux

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

Classification algorithms based on kernel nearest centers

A Julia package containing GNC algorithms for autonomous aerospace systems

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