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Https://stevengogogo.github.io/FindSteadyStates.jl/dev

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A julia package to implement model selection algorithms on basic regression models.

Symmetry-allowed k ⋅ p expansions

Alpha stable and sub-Gaussian distributions in Julia

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A Julia package for modelling Algorithmic Recourse Dynamics.

Causal Inference using Gaussian Processes with Structured Latent Confounders. Estimate treatment effects with Gaussian processes.

BioCCP.jl exploits the Coupon Collector Problem for sample size determination in combinatorial biotechnology.

Nonlinear diffusion problems in Julia

Anytime error minimization search for POMDPs, implemented in Julia.

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Algorithms for performing angular differential imaging (ADI)

Pipeline for debiasing and improving error bar estimates for photometry on top of structured/filamentary background.

Ground-motion simulation via the Stochastic Method

Stochastic distorted-wave Born approximation for acoustic scattering, in Julia

Extra non essential functionality for MixedModels.jl

Solver for complemetarity-based dynamics.

Differentiable acoustic ray tracers

An extension package of PowerModels.jl for Harmonic (Optimal) Power Network

Utilities to read/write extended GSLIB files in Julia

Http://proceedings.mlr.press/v119/bruinsma20a.html

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Drawing functions for `SimpleGraphs`

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Http://proceedings.mlr.press/v119/bruinsma20a.html

A Julia implementation of estimation and validation algorithms for time series compatible with incomplete data.

Reinforcement learning framework to find and analyze the likeliest failures of a system under test.

Plot critical difference diagrams in Julia

Implementation of a drone surveillance problem with POMDPs.jl

Conversions between Distributions.jl distributions and MeasureTheory.jl measures.

Mixed model solution for replicate designed bioequivalence study.

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Hypothesis tests of calibration.

Cumulants based features selection and outlier detection

Package for unfolding of complex 3-D geometries.

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 to compute the Distribution of Relaxation Times (DRT) of a given set of impedance measurements.

Bayesian addition to Flux.jl