About ===== Citing TieBeNN -------------- Ramos *et al.* (2026). A quasi-real-time system for automatic local event monitoring in Germany. *Seismica*, **5** (1). `https://doi.org/10.26443/seismica.v5i1.1815 `_ Acknowledgements ---------------- This project integrates, builds upon, and benefits from: - **NonLinLoc** - **SeisBench** - **PhaseNet**, **EQTransformer**, **DeepDenoiser**, which are open-source ML models integrated in **SeisBench** - **PyOcto** and **GaMMA** for phase association - Crustal models from several published studies (see full list in :doc:`velocity_models`) - Python packages and libraries maintained by the open-source community 💚 Special thanks to contributors, test users, and colleagues from the **Federal Seismological Service (EdB)** at BGR. License ------- TieBeNN is distributed under the **GNU General Public License v3.0 (GPLv3)**. .. code-block:: none This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or any later version. A copy of the full license is available in the LICENSE file. Links & availability ------------------------------------ - 🌐 **GitHub (public mirror)** https://github.com/Cthuulhaa/tiebenn.git The TieBeNN repository publicly available on GitHub for citation, installation, and issue reporting. - 📦 **Zenodo archive** https://doi.org/10.5281/zenodo.15825093 TieBeNN: A neural network-based tool for automatic focal depth estimation. Now archived on Zenodo for reproducible citation.