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Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components

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

Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

公众号【码农田小齐】的分类合集

Chemical reaction network and systems biology interface for scientific machine learning (SciML). High performance, GPU-parallelized, and O(1) solvers in open source software

Linear operators for discretizations of differential equations and scientific machine learning (SciML)

New home of Swift Development Environment for VS Code

Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem

Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem

The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems

Benchmarks for scientific machine learning (SciML) software and differential equation solvers

GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem

A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc.

A general platform for computational neuroscience and brain-inspired computation

Solving differential equations in R using DifferentialEquations.jl and the SciML Scientific Machine Learning ecosystem

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

A statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.

Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations

Solving linear, nonlinear equations, ordinary differential equations, ... using numerical methods in fortran

Build and simulate jump equations like Gillespie simulations and jump diffusions with constant and state-dependent rates and mix with differential equations and scientific machine learning (SciML)

A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations

Contrib package for Stable-Baselines3 - Experimental reinforcement learning (RL) code

Python package used for generating HTML reports about the contents of Esri geodatabases.

A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)

A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers

Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions