Neural Differential Equations ML Frameworks
Frameworks and implementations for Neural ODEs, Neural CDEs, Neural SDEs, and related neural operators that learn dynamics through differential equations. Includes solvers, applications to time series and PDEs, but does NOT include general deep learning frameworks, standard RNNs, or non-neural PDE solvers.
There are 111 neural differential equations frameworks tracked. 1 score above 70 (verified tier). The highest-rated is lululxvi/deepxde at 71/100 with 3,954 stars. 1 of the top 10 are actively maintained.
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| # | Framework | Score | Tier |
|---|---|---|---|
| 1 |
lululxvi/deepxde
A library for scientific machine learning and physics-informed learning |
|
Verified |
| 2 |
pnnl/neuromancer
Pytorch-based framework for solving parametric constrained optimization... |
|
Established |
| 3 |
wilsonrljr/sysidentpy
A Python Package For System Identification Using NARMAX Models |
|
Established |
| 4 |
dynamicslab/pysindy
A package for the sparse identification of nonlinear dynamical systems from data |
|
Established |
| 5 |
google-research/torchsde
Differentiable SDE solvers with GPU support and efficient sensitivity analysis. |
|
Established |
| 6 |
analysiscenter/pydens
PyDEns is a framework for solving Ordinary and Partial Differential... |
|
Established |
| 7 |
NeuroDiffGym/neurodiffeq
A library for solving differential equations using neural networks based on... |
|
Established |
| 8 |
arsedler9/lfads-torch
A PyTorch implementation of Latent Factor Analysis via Dynamical Systems... |
|
Established |
| 9 |
patrick-kidger/torchcde
Differentiable controlled differential equation solvers for PyTorch with GPU... |
|
Established |
| 10 |
NBoulle/greenlearning
Learning Green's functions of partial differential equations with deep learning. |
|
Established |
| 11 |
Tim-Salzmann/l4casadi
Use PyTorch Models with CasADi for data-driven optimization or... |
|
Established |
| 12 |
yataobian/awesome-ebm
Collecting research materials on energy/entropy based models |
|
Established |
| 13 |
jbramburger/DataDrivenDynSyst
Scripts and notebooks to accompany the book Data-Driven Methods for Dynamic Systems |
|
Established |
| 14 |
thuml/Neural-Solver-Library
A Library for Advanced Neural PDE Solvers. |
|
Established |
| 15 |
greydanus/hamiltonian-nn
Code for our paper "Hamiltonian Neural Networks" |
|
Established |
| 16 |
GaloisInc/dlkoopman
A general-purpose Python package for Koopman theory using deep learning. |
|
Established |
| 17 |
martenlienen/torchode
A parallel ODE solver for PyTorch |
|
Established |
| 18 |
scDiffEq/scdiffeq-analyses
Companion to https://github.com/scDiffEq/scDiffEq |
|
Established |
| 19 |
raminmh/CfC
Closed-form Continuous-time Neural Networks |
|
Emerging |
| 20 |
pswpswpsw/nif
A library for dimensionality reduction on spatial-temporal PDE |
|
Emerging |
| 21 |
aleximmer/Laplace
Laplace approximations for Deep Learning. |
|
Emerging |
| 22 |
Koopman-Laboratory/KoopmanLab
A library for Koopman Neural Operator with Pytorch. |
|
Emerging |
| 23 |
camlab-ethz/ConvolutionalNeuralOperator
This repository is the official implementation of the paper Convolutional... |
|
Emerging |
| 24 |
decargroup/pykoop
Koopman operator identification library in Python, compatible with `scikit-learn` |
|
Emerging |
| 25 |
vavrines/Kinetic.jl
Universal modeling and simulation of fluid mechanics upon machine learning.... |
|
Emerging |
| 26 |
SciML/HighDimPDE.jl
A Julia package for Deep Backwards Stochastic Differential Equation (Deep... |
|
Emerging |
| 27 |
EthanJamesLew/AutoKoopman
AutoKoopman - automated Koopman operator methods for data-driven dynamical... |
|
Emerging |
| 28 |
Zymrael/awesome-neural-ode
A collection of resources regarding the interplay between differential... |
|
Emerging |
| 29 |
DiffEqML/torchdyn
A PyTorch library entirely dedicated to neural differential equations,... |
|
Emerging |
| 30 |
cooper-org/cooper
A general-purpose, deep learning-first library for constrained optimization... |
|
Emerging |
| 31 |
IBM/simulai
A toolkit with data-driven pipelines for physics-informed machine learning. |
|
Emerging |
| 32 |
ctu-vras/monoforce
[IROS 2024] [ICML 2024 Workshop Differentiable Almost Everything] MonoForce:... |
|
Emerging |
| 33 |
xwinxu/bayeSDE
Code for "Infinitely Deep Bayesian Neural Networks with Stochastic... |
|
Emerging |
| 34 |
patrick-kidger/Deep-Signature-Transforms
Code for "Deep Signature Transforms" (NeurIPS 2019) |
|
Emerging |
| 35 |
patrick-kidger/NeuralCDE
Code for "Neural Controlled Differential Equations for Irregular Time... |
|
Emerging |
| 36 |
patrick-kidger/signatory
Differentiable computations of the signature and logsignature transforms, on... |
|
Emerging |
| 37 |
qiauil/torchfsm
TorchFSM: Fourier Spectral Method with PyTorch |
|
Emerging |
| 38 |
fregu856/ebms_regression
Official implementation of "Energy-Based Models for Deep Probabilistic... |
|
Emerging |
| 39 |
raj-gun/NonSysID
A MatLab package for System Identification using linear and nonlinear... |
|
Emerging |
| 40 |
samholt/NeuralLaplace
Neural Laplace: Differentiable Laplace Reconstructions for modelling any... |
|
Emerging |
| 41 |
thuml/Koopa
Code release for "Koopa: Learning Non-stationary Time Series Dynamics with... |
|
Emerging |
| 42 |
yriyazi/Koopman-Operator-and-Deep-Neural-Networks-ISAV2023
In this work, we present a novel approach that combines the power of... |
|
Emerging |
| 43 |
ODINN-SciML/DiffEqSensitivity-Review
A Review of Sensitivity Methods for Differential Equations |
|
Emerging |
| 44 |
AlexandraBaier/deepsysid
System identification toolkit for multistep prediction using deep learning... |
|
Emerging |
| 45 |
HaidaQuant/DeepBSDE
Python code for solving partial differential equations (PDEs) using deep... |
|
Emerging |
| 46 |
filippo-masi/Thermodynamics-Neural-Networks
Thermodynamics-based Artificial Neural Networks |
|
Emerging |
| 47 |
williamgilpin/fnn
Embed strange attractors using a regularizer for autoencoders |
|
Emerging |
| 48 |
PEREGRINE-GW/peregrine
A simulation-based Inference (SBI) library designed to perform analysis on a... |
|
Emerging |
| 49 |
qiauil/ConvDO
Convolutional Differential Operators for Physics-based Deep Learning Study |
|
Emerging |
| 50 |
slimgroup/FNO4CO2
Learned coupled inversion for carbon sequestration monitoring and... |
|
Emerging |
| 51 |
phy-q/benchmark
Phy-Q: A Testbed for Physical Reasoning |
|
Emerging |
| 52 |
DiffEqML/diffeqml-research
This repository contains code released by DiffEqML Research |
|
Emerging |
| 53 |
decargroup/closed_loop_koopman
Companion code for Closed-Loop Koopman Operator Approximation |
|
Emerging |
| 54 |
Hy23333/PFNN
Official implementation of Learning Dissipative Chaos In A Linear Way |
|
Emerging |
| 55 |
Midhun-Kanadan/Machine-Learning-Models-for-Topology-Optimization
This project explores the integration of Machine Learning (ML) and Deep... |
|
Emerging |
| 56 |
matlab-deep-learning/constrained-deep-learning
Constrained deep learning is an advanced approach to training deep neural... |
|
Emerging |
| 57 |
ELIFE-ASU/INNLab
A python/pytorch package for invertible neural networks |
|
Emerging |
| 58 |
peterparity/conservation-laws-manifold-learning
Discovering Conservation Laws using Optimal Transport and Manifold Learning |
|
Emerging |
| 59 |
Francis-Fan-create/SCaSML
ScaSML solver for high dimensional gradient dependent semilinear PDE |
|
Emerging |
| 60 |
halimarefat/torchFOAM
Using PyTorch within OpenFOAM |
|
Emerging |
| 61 |
Zheng-Meng/Dynamics-Reconstruction-ML
Published in Nature Communications: Bridging known and unknown dynamics by... |
|
Emerging |
| 62 |
Ranlot/single-parameter-fit
Real numbers, data science and chaos: How to fit any dataset with a single parameter |
|
Emerging |
| 63 |
HoangP8/torchidl
torchidl: a general library for implicit models |
|
Emerging |
| 64 |
Laborieux-Axel/holomorphic_eqprop
Repository to reproduce the results of the paper "Holomorphic Equilibrium... |
|
Emerging |
| 65 |
bizoffermark/neural_wos
Neural Walk-on-Spheres |
|
Emerging |
| 66 |
jambo6/neuralRDEs
Code for: "Neural Rough Differential Equations for Long Time Series", (ICML 2021) |
|
Emerging |
| 67 |
mbchang/dynamics
A Compositional Object-Based Approach to Learning Physical Dynamics |
|
Emerging |
| 68 |
Axect/Neural_Hamilton
Official implementation of the paper "Neural Hamilton: Can A.I. Understand... |
|
Emerging |
| 69 |
tomoleary/dino
Derivative-Informed Neural Operator: An Efficient Framework for... |
|
Emerging |
| 70 |
psellcam/LaplaceNet
A PyTorch Implementation of LaplaceNet:A Hybrid Energy-Neural Model for Deep... |
|
Emerging |
| 71 |
da03/Residual-EBM
Code for Residual Energy-Based Models for Text Generation in PyTorch. |
|
Emerging |
| 72 |
decargroup/robust_observer_koopman
Companion code for Uncertainty Modelling and Robust Observer Synthesis using... |
|
Experimental |
| 73 |
Zheng-Meng/Parameter-Tracking-with-Machine-Learning
Codes for ''Machine-learning parameter tracking with partial state... |
|
Experimental |
| 74 |
msakarvadia/operator_aliasing
Studying if/how alising happens when PDE solutions are learned at different... |
|
Experimental |
| 75 |
JakobEliasWagner/NeuralOperators
Neural Operators with Applications to the Helmholtz Equation |
|
Experimental |
| 76 |
ameya98/ActionAngleNetworks
The official JAX implementation of Action-Angle Networks! |
|
Experimental |
| 77 |
jambo6/online-neural-cdes
Code for: "Neural Controlled Differential Equations for Online Prediction Tasks" |
|
Experimental |
| 78 |
filippo-masi/NICE
Neural integration for constitutive equations |
|
Experimental |
| 79 |
dimitra-maoutsa/odes_for_sdes
Deterministic particle dynamics for simulating Fokker-Planck probability flows |
|
Experimental |
| 80 |
pz33y/SynechismCore
Stabilized Neural ODEs outperform Transformers on spatiotemporal chaos... |
|
Experimental |
| 81 |
tsuboshun/LearnEntropy
This repository estimates the entropy production rate from trajectory data... |
|
Experimental |
| 82 |
YichengDWu/NeuralGraphPDE.jl
Integrating Neural Ordinary Differential Equations, the Method of Lines, and... |
|
Experimental |
| 83 |
haozhg/odmd-matlab
Matlab implementation of online and window dynamic mode decomposition algorithms |
|
Experimental |
| 84 |
liuyao12/ConvNets-PDE-perspective
an Open Collaborative project to explore the implications — theoretical or... |
|
Experimental |
| 85 |
kaist-silab/awesome-graph-pde
Collection of resources about partial differential equations, graph neural... |
|
Experimental |
| 86 |
TOAQ-oss/nonlinear-affective-dynamics
Official implementation of the paper "Non-Linear Computational Modeling of... |
|
Experimental |
| 87 |
Alexin-CH/ReflectorML
Hybrid ML/PIML freeform reflector design |
|
Experimental |
| 88 |
NiuTrans/ODEs-in-Vision-and-Language
An introduction to ODEs and their applications in vision and language |
|
Experimental |
| 89 |
Emory-Melody/awesome-epidemic-modeling-papers
[KDD 2024] Papers about deep learning in epidemic modeling. |
|
Experimental |
| 90 |
NekkittAY/DMD-Neural-Operator
DMD Neural Operator - A neural operator using DMD analysis to approximate the PDEs |
|
Experimental |
| 91 |
anac0der/fno_from_scratch
Implementation of Fourier Neural Operator from scratch |
|
Experimental |
| 92 |
pcpet/intervalNets
Interval arithmetic toolkit for PyTorch with certified interval forward... |
|
Experimental |
| 93 |
1ksev/Dynamic-Systems-Analysis
🏎️ Model and simulate vehicle suspension dynamics using Python and Laplace... |
|
Experimental |
| 94 |
timkimd/plnde
Code for "Inferring Latent Dynamics Underlying Neural Population Activity... |
|
Experimental |
| 95 |
eth-siplab/Frequency-weighted-neural-Kalman-filters
FW-NKF: Frequency-Weighted Neural Kalman Filters -- Official implementation.... |
|
Experimental |
| 96 |
erik2810/differentiable-physics-engine
Browser-based differentiable physics demo: neural network learns and... |
|
Experimental |
| 97 |
dandip/ssinn
Code for the paper "Sparse Symplectically Integrated Neural Networks" |
|
Experimental |
| 98 |
lmotte/controlled-sde-learn
Python implementation of the SDE estimation method proposed in... |
|
Experimental |
| 99 |
pvlachas/LearningEffectiveDynamics
Framework to learn effective dynamics and couple a macro scale simulator... |
|
Experimental |
| 100 |
Shraddha22710/SKOOP-RED
Official code for the IEEE SPL paper "Stabilizing RED using the Koopman... |
|
Experimental |
| 101 |
junetroan/Deep-Learning-Strategies
Code developed for the authors master's thesis "Novel Deep Learning... |
|
Experimental |
| 102 |
enochkan/kalmanpy
Implementation of Kalman Filter in Python |
|
Experimental |
| 103 |
benettia/phaseflux
Ever wondered what happens when gas and liquid mix inside a tube? |
|
Experimental |
| 104 |
Northeastern-Research-ORNL-1/pyreflect-interface
A minimal, monochrome web interface for the pyreflect neutron reflectivity... |
|
Experimental |
| 105 |
LeiMinghaoSJTU/neural-operators
深度学习求解PDE:神经算子 中文示例Notebook |
|
Experimental |
| 106 |
dantor03/daudin-delarue-moons
Empirical verification of Daudin & Delarue (2025): mean-field Neural ODEs... |
|
Experimental |
| 107 |
Zylus08/Neural-Surrogate-Monte-Carlo-Collision-Simulator
Hybrid Monte Carlo + Neural surrogate simulator for high-energy particle... |
|
Experimental |
| 108 |
LaoZhongjie/lstm-chaos-dynamics
A research project investigating how LSTM training dynamics relate to... |
|
Experimental |
| 109 |
Lingkai-Kong/so-ebm
Code for paper: End-to-end Stochastic Optimization with Energy-based Model |
|
Experimental |
| 110 |
EdWangLoDaSc/DSOVT
Sample codes for training of dynamical system prediction from sparse... |
|
Experimental |
| 111 |
mschossler/fluctuationRelations
Fluctuations are important for systems with a small number of degrees of... |
|
Experimental |