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Koopman Learning Code

This folder contains Python code for two stage Koopman learning using PyTorch.

Prerequisites

Before you begin, ensure you have met the following requirements:

  • Python 3.x
  • PyTorch
  • Other required libraries (please refer to the requirements.txt file)

Getting Started

To get started with this code, follow these steps:

  1. Clone this repository:

    git clone https://github.com/your-username/koopman-learning.git
cd koopman-learning

  2. Install the required dependencies:

    pip install -r requirements.txt

  3. Run the Koopman learning code by executing the main script:

    python main.py

Code Overview

Loss Calculation

The code includes a function cacl_loss_Koopman for calculating the Koopman loss. This function takes various parameters and performs Koopman learning. It computes the loss using Mean Squared Error (MSE) and updates the model accordingly.

Configuration

You can configure the Koopman learning process by modifying the parameters in the config.yaml. Additionally, you can adjust the neural network architecture in the config.yaml file also.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

  • Special thanks to the contributors and the PyTorch community.