CurricularVisualization.jl is an extension of the CurricularAnalytics.jl toolbox for visualizing curricula and degree plans.

Provides proximal operator evaluation routines and proximal optimization algorithms, such as (accelerated) proximal gradient methods and alternating direction method of multipliers (ADMM), for non-smooth/non-differentiable objective functions.

[WIP]: QEDprocesses.jl: Modeling of scattering processes for QED.jl

A Julia package for simulating the dynamics of passively crosslinked actin rings.

Radial Basis Function Surrogates

Multi-language suite for analyzing calibration of probabilistic predictive models.

Points and lines in the projective plane (with rational homogenous coordinates)

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An easy to use implementation of the Branch Flow Model using JuMP for optimal power flow problems

Computes the boundary crossing probability for a general diffusion process and time-dependent boundary.

A Julia package for simulating Social Sampling Theory

A Julia package for statistical modeling of binned data, e.g. histograms.

A reverse McCormick operator library

Core API of BAT.jl

A package for generating and analyzing Aztec diamonds

Romeo Occupation Matrix Energy Optimizer for DFT

Algorithms for Risk Parity and Risk Budgeting portfolios for CV@R, using simulated scenarios

🪴 example of root system architecture simulation like CRootBox

Small package to extract coordinates of countries border

Particle methods for 1D conservation laws

Compactly supported basis functions in Julia

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Evaluate catchaMouse16 features in Julia

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Reading and writing Bundler files with Julia

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A package for discretizing trajectory data into a transition probability matrix using Ulam's method.

Adversarial Attack Tool for Knet

A Julia package for Tomography.

Deep Unfolded Convolutional Dictionary Learning for motif discovery.

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Julia simulation package for TKTD models

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Adds support for parallelization for Taija packages.

Quadratic approximation of posterior distribution using StanOptimize

Simple predictive models for tumor growth, and tools to apply them to clinical data