Referencing Guide

SeisBench is a collaborative project that builds on contributions from many researchers. When using SeisBench, you typically rely on work from different authors. This guide outlines which publications to cite for common use cases.

Applying a Pretrained Model

If you are applying a pretrained model, please cite:

  • SeisBench

  • The model architecture (see model.citation attribute)

  • The publication describing the trained weights (see model.weights_docstring attribute).

  • The publication describing the training dataset

Example statement

“We use PhaseNet [1] implemented in SeisBench [2] trained on the INSTANCE dataset [3, 4].”

Using a Dataset

If you are using a dataset provided through SeisBench, please cite:

  • SeisBench

  • The dataset publication

Example statement

“We use the INSTANCE dataset [1] accessed through SeisBench [2].”

Training a Model

If you are training your own model, please cite:

  • SeisBench

  • The model architecture

  • The training dataset

Example statement

“We train the PhaseNet model [1], implemented in SeisBench [2], on the INSTANCE dataset [3].”

Closing Remarks

Proper citation is essential to give credit to the original authors and to support continued development of methods and software. In many cases, you should also consider citing ObsPy, as it is underlies SeisBench and is commonly used alongside SeisBench.