Simple differential equation solvers in native Julia for scientific machine learning (SciML)

Symbolic-Numeric Universal Differential Equations for Automating Scientific Machine Learning (SciML)

A julia package to either fit the parameters of a specified equivalent electrical circuit to electrochemical impedance data, or to suggest a plausible circuit configuration for a given set of measurements (either through a comparison of circuits from the literature, or through an evolutionary algorithm approach).

Iterative hard thresholding for l0 penalized regression

Plotly integration for Stipple.jl

Package for Bayesian and classical estimation and inference based on statistics that are filtered through a trained neural net

Tools for simulating organism dispersal

Generate and perturb protein structural ensembles using the ExProSE algorithm

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One stop solutions for all things optimization

Constrained and NoNlinear Optimizer of Least Squares

Implementations of Infinitesimal Continuous Normalizing Flows Algorithms in Julia

Data and functions to support Julia projects based on the book "Regression and Other Stories" by Andrew Gelman, Jennifer Hill and Aki Vehtari.

Solvers for problems involving unsteady fluid flow

An open-source toolkit for entropic data analysis

Abstraction layer for spanning factor graphs over various technologies

Building blocks for simple and advanced particle filtering in Gen.

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A package for computing integrals over domains like they are defined in DomainSets.jl.

Large scale convex optimization solvers in julia

Iterators with message passing and feedback loops

DINCAE (Data-Interpolating Convolutional Auto-Encoder) is a neural network to reconstruct missing data in satellite observations.

Julia package for general many-body exact diagonalization calculation.

Julia Package for computing [controlled] invariant sets of Hybrid Systems using Sum Of Squares Programming

An energy system optimization model that is flexible, computationally efficient, and academically robust.

A Meta Package for Machine Learning Interpretation

Analysis, processing, and simulation of data generated by scientific robots in the Ocean.

A fast module for computing proximity queries between convex bodies in 2D/3D

Package for computing pressure profiles for gas lift optimization of oil & gas wells.

Turbulence-resolving simulations of boundary-layer flows (DNS & LES)

Differentiable tree-based models for tabular data

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Electrochemical reaction rate modeling and nonequilibrium phase maps (via AD)

A Julia package for random variables, some transformations and probabilities

Families of polynomials

Wrappers for the SciPy differential equation solvers for the SciML Scientific Machine Learning organization

Useful Layers for Knet

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A Julia package to simulate light propagation in optical systems

Markov Chain Monte Carlo convergence diagnostics in Julia