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A Julia package for behavioural modeling

Julia Package for Active Inference

Common functions in actuarial and financial routines

Generalized linear models for cell-cell communication

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[WIP] Wrapper package for simulation and bayesian inference of behavioral models

Repository for the BarBay Julia package for Bayesian inference of relative fitness on barcode sequencing data.

BOSS (Bayesian Optimization with Semiparametric Surrogate)

Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia

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Extension functionality which uses Stan.jl, DynamicHMC.jl, and Turing.jl to estimate the parameters to differential equations and perform Bayesian probabilistic scientific machine learning

Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.

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Differentiable JUlia ICE model

Optimal experimental design of ODE and DAE systems in julia

High level functions for analyzing the output of simulations

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Composable contracts, models, and functions that allow for modeling of both simple and complex financial instruments

Geometry optimization for molecular simulation

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The Julia implementation of the generalised hierarchical Gaussian filter

Fast and flexible glacier ice flow models

Methods for computational information geometry

Symmetry-allowed k ⋅ p expansions

Ecosystem of numerical methods for microbial kinetics data analysis, from preprocessing to result interpretation.

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

Lightweight module of neural differential equations in Kinetic.jl

Marginalized log-probability functions in Julia

Julia implementation of maximum entropy graph models

Methods for the evaluation of maximum entropy distributions

Comparing performance and results of mcmc options using Julia

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

Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation

Noise modeling

Octofitter is a Julia package for performing Bayesian inference against direct images of exoplanets, relative astrometry, and astrometric acceleration of the host star.

Mathematical Optimization in Julia. Local, global, gradient-based and derivative-free. Linear, Quadratic, Convex, Mixed-Integer, and Nonlinear Optimization in one simple, fast, and differentiable interface.

The base package for Optimization.jl, containing the structs and basic functions for it.

Preheat your MCMC

The julia library for the peccon project