AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
翻译准备中
Physics-Informed Neural Networks (PINN) Solvers of (Partial) Differential Equations for Scientific Machine Learning (SciML) accelerated simulation
翻译准备中
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正在加载完整 README。 以下为已保存的摘录。
NeuralPDE.jl is a solver package which consists of neural network solvers for
partial differential equations using physics-informed neural networks (PINNs). This package utilizes
neural stochastic differential equations to solve PDEs at a greatly increased generality
compared with classical methods.
Assuming that you already have Julia correctly installed, it suffices to install NeuralPDE.jl in the standard way, that is, by typing ] add NeuralPDE. Note:
to exit the Pkg REPL-mode, just press Backspace or Ctrl + C .查看完整 README ↗目前无法加载完整 README。请通过原文链接阅读。 以下为已保存的摘录。
NeuralPDE.jl is a solver package which consists of neural network solvers for
partial differential equations using physics-informed neural networks (PINNs). This package utilizes
neural stochastic differential equations to solve PDEs at a greatly increased generality
compared with classical methods.
Assuming that you already have Julia correctly installed, it suffices to install NeuralPDE.jl in the standard way, that is, by typing ] add NeuralPDE. Note:
to exit the Pkg REPL-mode, just press Backspace or Ctrl + C .查看完整 README ↗