40 Open Source Neural Ode Software Projects
Free and open source neural ode code projects including engines, APIs, generators, and tools.
Diffeqflux.jl 647 ⭐
Universal neural differential equations with O(1) backprop, GPUs, and stiff+non-stiff DE solvers, demonstrating scientific machine learning (SciML) and physics-informed machine learning methods
Modelingtoolkit.jl 932 ⭐
A modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
Neural Ode 399 ⭐
Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations
Scimltutorials.jl 585 ⭐
Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
Tfdiffeq 187 ⭐
Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support
Ode.jl 98 ⭐
Assorted basic Ordinary Differential Equation solvers for scientific machine learning (SciML)
Diffeqoperators.jl 235 ⭐
Linear operators for discretizations of differential equations and scientific machine learning (SciML)
Diffeqdocs.jl 171 ⭐
Documentation for the DiffEq differential equations and scientific machine learning (SciML) ecosystem
Scimlbenchmarks.jl 167 ⭐
Benchmarks for scientific machine learning (SciML) software and differential equation solvers
Diffeqbase.jl 173 ⭐
The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
Diffeqbayes.jl 103 ⭐
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
Universal_differential_equations 155 ⭐
Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high performance SciML
Diffeqgpu.jl 121 ⭐
GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
Diffeqsensitivity.jl 151 ⭐
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.
Multiscalearrays.jl 56 ⭐
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
Diffeqparamestim.jl 35 ⭐
Easy scientific machine learning (SciML) parameter estimation with pre-built loss functions
Diffeqcallbacks.jl 37 ⭐
A library of useful callbacks for hybrid scientific machine learning (SciML) with augmented differential equation solvers
Diffeqjump.jl 58 ⭐
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)
Optimalcontrol.jl 20 ⭐
A component of the SciML scientific machine learning ecosystem for optimal control
Boundaryvaluediffeq.jl 20 ⭐
Boundary value problem (BVP) solvers for scientific machine learning (SciML)
Diffeqproblemlibrary.jl 24 ⭐
A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools
Neural Ode Norm 14 ⭐
Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"
Torchcde 219 ⭐
Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
Torchdyn 745 ⭐
A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods.
Bayesian Sde 99 ⭐
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
Neural Ode Metasolver 25 ⭐
Supplementary code for the paper "Meta-Solver for Neural Ordinary Differential Equations" https://arxiv.org/abs/2103.08561
Regneuralde.jl 22 ⭐
Official Implementation of "Opening the Blackbox: Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics" (ICML 2021)
Lpdc Net 21 ⭐
CVPR2021 paper "Learning Parallel Dense Correspondence from Spatio-Temporal Descriptorsfor Efficient and Robust 4D Reconstruction"
Control Of Stochastic Quantum Dynamics With Differentiable Programming 12 ⭐
Repository for the Control of Stochastic Quantum Dynamics with Differentiable Programming paper.