SciMLBenchmarks
Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R
JumpProcesses
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)
scimlbook
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
DiffEqBase
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
BoundaryValueDiffEq
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
SciMLSensitivity
A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, adjoint methods, and more for ODEs, SDEs, DDEs, DAEs, etc.
DiffEqFlux
Pre-built implicit layer architectures with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
SciMLTutorials
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
DiffEqParamEstim
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
MultiScaleArrays
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
DiffEqBayes
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
DiffEqCallbacks
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
BVProblemLibrary
A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools
diffeqdocs.jl
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
torchdyn
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods
coarsegrained-md-neural-ode
Thesis repository on neural ordinary differential equations used for coarse-graining molecular dynamics
scimltutorialsoutput
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
https://github.com/avik-pal/regneuralde.jl
Official Implementation of "Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics" (ICML 2021)
neural-ode-ion-channels
Code and figures for "Neural network differential equations for ion channel modelling".
https://github.com/chenliu-1996/imageflownet
[ICASSP 2025 Oral] ImageFlowNet: Forecasting Multiscale Image-Level Trajectories of Disease Progression with Irregularly-Sampled Longitudinal Medical Images
BridgeDiffEq
A thin wrapper over Bridge.jl for the SciML scientific machine learning common interface, enabling new methods for neural stochastic differential equations (neural SDEs)