VAGANBoost

Introduction

VAGANBoost is a hybrid generative model combining Variational Autoencoders (VAE) and Generative Adversarial Networks (GAN) with boosting techniques to enhance high-energy gamma-ray analysis.

Features

• Implements VAE+GAN and LGBM models
• Designed for high-energy physics applications
• Utilizes deep learning and gradient boosting techniques

Installation

pip install vaganboost

Usage

from vaganboost import train
train.run()

Dependencies

See requirements.txt for required packages.

License

This project is licensed under the MIT License.

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| https://github.com/AliBavarchee/ |

| https://www.linkedin.com/in/ali-bavarchee-qip/ |