neural-ode 开源项目推荐（168 个）

SciML /SciMLBook

并行计算和科学机器学习（SciML）：方法和应用（MIT 18.337J/6.338J）

DiffEqML /torchdyn

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

raminmh /CfC

Closed-form Continuous-time Neural Networks

SciML /DiffEqFlux.jl

预构建隐式层架构，采用O（1）反向推进、GPU和stiff+non刚性微分方程求解器，展示了科学机器学习（SciML）和物理知情机器学习方法

msurtsukov /neural-ode

Jupyter notebook with Pytorch implementation of Neural Ordinary Differential Equations

SciML /SciMLTutorials.jl

使用开源软件进行科学机器学习（SciML）和高性能微分方程求解的教程。

SciML /SciMLSensitivity.jl

DiffEq 生态系统的一个组件，用于为科学机器学习（SciML）启用敏感性分析。包括先优化后离散、先离散后优化、伴随方法等，适用于 ODE、SDE、DDE、DAE 等。

SciML /ComponentArrays.jl

具有任意嵌套命名组件的数组。

SciML /DiffEqBase.jl

轻量级基础库，提供用于定义微分方程与科学机器学习（SciML）问题的共享类型和功能

SciML /SciMLBenchmarks.jl

科学机器学习（SciML）基准、面向科学的 AI 以及（微分）方程求解器。涵盖 Julia、Python（PyTorch、Jax）、MATLAB、R

SciML /DiffEqDocs.jl

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

SciML /DiffEqGPU.jl

用于 DifferentialEquations.jl 及更广泛的 SciML 科学机器学习生态系统的 GPU 加速例程

mitmath /18S096SciML

18.S096 - Applications of Scientific Machine Learning

jacobjinkelly /easy-neural-ode

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

martenlienen /torchode

A parallel ODE solver for PyTorch

SciML /DiffEqOperators.jl

用于微分方程离散化和科学机器学习（SciML）的线性算子。

ChrisRackauckas /universal_differential_equations

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

titu1994 /tfdiffeq

全GPU支持的常微分方程求解器的张量流实现

Zymrael /gde

Neural Graph Differential Equations (Neural GDEs)

xwinxu /bayeSDE

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