- Keywords: Seismology, GAN, conditional generation, signal processing
- TL;DR: Using Generative Adversarial Networks we demonstrate how one can create a seismic signal from the earthquake that has never existed.
- Abstract: This study applies Conditional Generative Adversarial Networks (cGAN) to the field of seismology. With GAN, realistic seismic waveforms can be created for various applications, such as augmenting limited seismic data or modeling, or generating realistic noise. A potential and alarming application of GAN is to generate realistic seismic signals that can cause disturbances to the international treaty banning nuclear explosions (CTBT). Results show that the generated seismic waves are nearly indistinguishable from real ones.
- Track: Original Research Track