Implementation of Guided Proposals (introduced by M Schauer, F van der Meulen, H van Zanten)

A framework for simulating dynamical structures coupling with viscous incompressible flows

Julia simulation package for TKTD models

Trace estimation methods for matrix functions.

State space reconstruction (SSR) for the study of dynamical system from time series.

Estimating the transfer operator (Perron Frobenius operator) and invariant measures from time series.

Base functionality used throughout the CausalityTools ecosystem

Observable for Markov chain Monte Carlo simulations

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

Makie visualization module for TopOpt.jl

SossMLJ makes it easy to build MLJ machines from user-defined models from the Soss probabilistic programming language

Image analysis and stochastic processes on shape and landmark spaces.

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

Julia package for different types of asset return or price models

Differentiable neural network with easy access to Jacobians of the output wrt the input and the network parameters.

Simulate Machine Learning-based Business Processes in Julia

Simulating zonal flows on the β-plane.

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Comparing performance and results of mcmc options using Julia

Reweighting survey data so that it sums to some target totals.

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Trust-region methods with partitioned quasi-Newton approximations

Valid Discrete-Time Methods for Relaxing pODEs

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A Julia package containing GNC algorithms for autonomous aerospace systems

A dynamically-structured matrix population model

Repository for the Julia BOMBS package

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Differential Inequality Algorithms for Parametric ODEs

Methods for the evaluation of maximum entropy distributions

Monte Carlo simulation routines for high-performance parallelization of differential equation solvers and scientific machine learning

Deprecated package (use instead Modia.jl)

Deprecated package (use instead Modia.jl)

Epidemic spatial and temporal model setup and simulation. Focusing on state of the art epidemiology models such as universal differential equations, epidemiology-informed deep learning models. Part of Mathepia.jl

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Abstraction Layer for Dynamic Bounds

Time stepping for Gridap

A wrapper for the Python PyDSTool library for the SciML Scientific Machine Learning organization