This paper reviews the progress in geoacoustic inversion over the past several decades.
The review is separated into two parts. The first part reviews developments in model-based …

Non-linear inverse problems in the geosciences often involve probabilistic sampling of
multimodal density functions or global optimization and sometimes both. Efficient algorithmic …

Seismological observations reveal patches of low-velocity anomalies at the core–mantle
boundary known as ultralow-velocity zones. Despite recent advances, their origin and …

The Bayesian earthquake analysis tool (BEAT) is an open‐source Python software to
conduct source‐parameter estimation studies for crustal deformation events, such as …

Seismic surface wave tomography is a tried and tested method to reveal the subsurface
structure of the Earth. However, the conventional 2-step scheme of inverting first for 2-D …

This paper considers the efficiency of trans-dimensional (trans-D) Bayesian inversion based
on reversible-jump Markov-chain Monte Carlo (rjMCMC) sampling, with application to …

This paper develops a probabilistic Bayesian approach to the problem of inferring the
spatiotemporal evolution of earthquake rupture on a fault surface from seismic data with …

This paper develops an efficient hierarchical trans-dimensional (trans-D) Bayesian algorithm
to invert magnetotelluric (MT) data for subsurface geoelectrical structure, with unknown …

Depth-dependent geoacoustic properties are inferred from wide-angle frequency-domain
reflection-coefficient data at two sites with different mud-layer thicknesses on the New …

In geophysical inversion, inferences of Earth's properties from sparse data involve a trade-off
between model complexity and the spatial resolving power. A recent Markov chain Monte …