ai4plasma

Getting Started

  • 1. Installation Guide
  • 2. Quick Start
  • 3. Basic Concepts
  • 4. Configuration

User Guide

  • 1. Physics-Informed Machine Learning (PIML)
  • 2. Neural Operators
  • 3. Training, Logging, Checkpoints
  • 4. Utilities
  • 5. Plasma Models

Examples

  • 1. Physics-Informed Machine Learning (PIML)
  • 2. Operator Learning
  • 3. Plasma Simulation

Core Modules

  • 1. Core Module
  • 2. Physics-Informed Machine Learning (PIML)
  • 3. Operator Learning Module
  • 4. Plasma Physics Module
  • 5. Utilities

Development

  • 1. Contributing
ai4plasma
  • API Reference
  • View page source

API Reference

This section details the API of the AI4Plasma package.

Modules

  • 1. Core Module
    • 1.1. Model
    • 1.2. Network
  • 2. Physics-Informed Machine Learning (PIML)
    • 2.1. Geometry
    • 2.2. PINN
    • 2.3. CS-PINN (Conservative PINN)
    • 2.4. RK-PINN (Runge-Kutta PINN)
    • 2.5. Meta-PINN (Meta-Learning PINN)
    • 2.6. NAS-PINN (Neural Architecture Search for PINN)
  • 3. Operator Learning Module
    • 3.1. DeepONet
    • 3.2. DeepCSNet
  • 4. Plasma Physics Module
    • 4.1. Properties
    • 4.2. Arc Discharge
  • 5. Utilities
    • 5.1. Common
    • 5.2. Math
    • 5.3. Device
    • 5.4. I/O

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