neural-ode

There are 93 repositories under neural-ode topic.

  • SciML/SciMLBook

    Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

    Language:HTML1.9k6343357

  • DiffEqML/torchdyn

    A PyTorch library entirely dedicated to neural differential equations, implicit models and related numerical methods

    Language:Jupyter Notebook1.5k28114134

  • raminmh/CfC

    Closed-form Continuous-time Neural Networks

    Language:Python9843217158

  • SciML/DiffEqFlux.jl

    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

    Language:Julia90127402161

  • msurtsukov/neural-ode

    Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations

    Language:Jupyter Notebook784124129

  • SciML/SciMLTutorials.jl

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

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  • SciML/SciMLSensitivity.jl

    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.

    Language:Julia3691737080

  • SciML/DiffEqBase.jl

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

    Language:Julia34815234120
  • ComponentArrays.jl

    SciML/ComponentArrays.jl

    Arrays with arbitrarily nested named components.

    Language:Julia337218939

  • SciML/SciMLBenchmarks.jl

    Scientific machine learning (SciML) benchmarks, AI for science, and (differential) equation solvers. Covers Julia, Python (PyTorch, Jax), MATLAB, R

    Language:MATLAB3341393101

  • SciML/DiffEqDocs.jl

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

    Language:Julia31714178254

  • mitmath/18S096SciML

    18.S096 - Applications of Scientific Machine Learning

    Language:HTML31122249

  • SciML/DiffEqGPU.jl

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

    Language:Julia31089238
  • easy-neural-ode

    jacobjinkelly/easy-neural-ode

    Code for the paper "Learning Differential Equations that are Easy to Solve"

    Language:Python2848828

  • SciML/DiffEqOperators.jl

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

    Language:Julia2841519572

  • martenlienen/torchode

    A parallel ODE solver for PyTorch

    Language:Python27014520

  • ChrisRackauckas/universal_differential_equations

    Repository for the Universal Differential Equations for Scientific Machine Learning paper, describing a computational basis for high performance SciML

    Language:Julia233182360

  • titu1994/tfdiffeq

    Tensorflow implementation of Ordinary Differential Equation Solvers with full GPU support

    Language:Python223101253

  • Zymrael/gde

    Neural Graph Differential Equations (Neural GDEs)

    Language:Jupyter Notebook2086233

  • xwinxu/bayeSDE

    Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"

    Language:Python1707128

  • SciML/JumpProcesses.jl

    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)

    Language:Julia147818438

  • SciML/DiffEqBayes.jl

    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

    Language:Julia125107028

  • SciML/ODE.jl

    Assorted basic Ordinary Differential Equation solvers for scientific machine learning (SciML). Deprecated: Use DifferentialEquations.jl instead.

    Language:Julia103186647

  • SciML/DiffEqCallbacks.jl

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

    Language:Julia10027154

  • DENG-MIT/CRNN

    Chemical Reaction Neural Network

    Language:Julia967723

  • sangyun884/fast-ode

    Official PyTorch implementation for the paper Minimizing Trajectory Curvature of ODE-based Generative Models, ICML 2023

    Language:Python88136

  • SciML/DiffEqProblemLibrary.jl

    A library of premade problems for examples and testing differential equation solvers and other SciML scientific machine learning tools

    Language:Julia8542538

  • cfinlay/ffjord-rnode

    Regularized Neural ODEs (RNODE)

    Language:Python842515

  • SciML/MultiScaleArrays.jl

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

    Language:Julia7743218

  • martenlienen/finite-element-networks

    Reference implementation of Finite Element Networks as proposed in "Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks" at ICLR 2022

    Language:Jupyter Notebook69224

  • jason71995/Keras_ODENet

    Implementation of (2018) Neural Ordinary Differential Equations on Keras

    Language:Python664619

  • SciML/sciml.ai

    The SciML Scientific Machine Learning Software Organization Website

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  • SciML/DiffEqParamEstim.jl

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

    Language:Julia6258133

  • SciML/BoundaryValueDiffEq.jl

    Boundary value problem (BVP) solvers for scientific machine learning (SciML)

    Language:Julia52810440

  • thaipduong/SE3HamDL

    Code for our RSS'21 paper: "Hamiltonian-based Neural ODE Networks on the SE(3) Manifold For Dynamics Learning and Control"

    Language:Python462012

  • gabrevaya/LatentDiffEq.jl

    Latent Differential Equations models in Julia.

    Language:Julia38527