Full‐waveform inversion (FWI) is today a standard process for the inverse problem of
seismic imaging. PDE‐constrained optimization is used to determine unknown parameters …

The Wasserstein metric is broadly used in optimal transport for comparing two probabilistic
distributions, with successful applications in various fields such as machine learning, signal …

This work characterizes, analytically and numerically, two major effects of the quadratic
Wasserstein (W 2) distance as the measure of data discrepancy in computational solutions …

Extracting physical parameters that cannot be directly measured from an observed data set
remains a great challenge in several fields of science and physics. In many of these …

In our previous work (Liao et al. in Commun Math Sci, 2022), the complexity of Sinkhorn
iteration is reduced from O (N 2) to the optimal O (N) by leveraging the special structure of …

Reliable density information is an essential factor in lithologic interpretation and reservoir
evaluation. However, density reconstruction is hampered by a lack of long-wavelength …

Full waveform inversion (FWI) aims at reconstructing unknown physical coefficients in wave
equations using the wave field data generated from multiple incoming sources. In this work …

We study the Wasserstein natural gradient in parametric statistical models with continuous
sample spaces. Our approach is to pull back the L^ 2 L 2-Wasserstein metric tensor in the …

Capacity constrained optimal transport is a variant of optimal transport, which adds extra
constraints on the set of feasible couplings in the original optimal transport problem to limit …

Full waveform inversion (FWI) has recently become a favorite technique for the inverse
problem of finding properties in the earth from measurements of vibrations of seismic waves …