14 citations · 32 across the 7 of their papers we have counts for
5 papers · 1 filter
Large-scale bioacoustic detection using semantic segmentation: a deep learning framework applied to fin whale calls in ocean-bottom seismometer recordings
Jocelyn Japnanto, Alex A. Saoulis, Miriam Romagosa +5
Ocean-bottom seismometers (OBS), originally deployed for geophysical research, continuously record low-frequency sound for months to years across broad areas of ocean, offering a l…
Improving moment tensor solutions under Earth structure uncertainty with simulation-based inference
A. A. Saoulis, T. -S. Pham, A. M. G. Ferreira
Bayesian inference represents a principled way to incorporate Earth structure uncertainty in full-waveform moment tensor inversions, but traditional approaches generally require si…
Full-waveform earthquake source inversion using simulation-based inference
A. A. Saoulis, D. Piras, A. Spurio Mancini +2
This paper presents a novel framework for full-waveform seismic source inversion using simulation-based inference (SBI). Traditional probabilistic approaches often rely on simplify…
Towards fast machine-learning-assisted Bayesian posterior inference of microseismic event location and source mechanism
Davide Piras, Alessio Spurio Mancini, Ana M. G. Ferreira +2
Bayesian inference applied to microseismic activity monitoring allows the accurate location of microseismic events from recorded seismograms and the estimation of the associated un…
Accelerating Bayesian microseismic event location with deep learning
A. Spurio Mancini, D. Piras, A. M. G. Ferreira +2
We present a series of new open source deep learning algorithms to accelerate Bayesian full waveform point source inversion of microseismic events. Inferring the joint posterior pr…