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

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

Connecting MLJ and MLFlow

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

Fast accurate creation, detection and analysis of quantum vortex distributions.

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Regulatory networks

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A Package for Estimating Stochastic Frontier Models using Julia

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

A Julia package for kernel functions of Method of Moments (MoM) and Multi-level Fast Multipole Algorithm (MLFMA).

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

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Neural-Network Outlier Detection Algorithms for Julia

A Julia based implementation of Plug and Play Language Models

Julia package for MPI reconstruction

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Forked Successor to github.com/JuliaFolds/FLoops.jl

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

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Tools to specify and simulate individual based models, using applied category theory

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

A Julia package for modelling Algorithmic Recourse Dynamics.

Bayesian addition to Flux.jl

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Layerwise Relevance Propagation in Julia.

MPI based parallel for method of moments (MoM) and MLFMA (https://github.com/deltaeecs/MoM_AllinOne.jl.jl)

A Julia package for integration of packages of Method of Moments (MoM) and Multi-level Fast Multipole Algorithm (MLFMA).

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

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

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

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

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