Why do people make the choices they do? Researchers from the Center Synergy of Systems (SynoSys) at TUD Dresden University of Technology, the Max Planck Institute for Human Development, and the ...

Inverse electromagnetic (EM) modeling plays a pivotal role in subsurface exploration, enabling the characterization of the Earth’s electrical properties for various applications, including resource ...

GeoBO is build upon a probabilistic framework using Gaussian Process (GP) priors to jointly solve multi-linear forward models. This software generates multi-output 3D cubes of geophysical properties ...

Scientists at Lawrence Livermore National Laboratory (LLNL) have helped develop an advanced, real-time tsunami forecasting system — powered by El Capitan, the world’s fastest supercomputer — that ...

Abstract: Estimating flaw profiles from measurements is a typical inverse problem in electromagnetic nondestructive evaluation (NDE). This paper proposes a novel state-space approach for solving such ...

This project turns score-based diffusion models into explicit priors for Bayesian inverse problems in imaging. A "score-based prior" allows us to model complex, data-driven posterior distributions ...

Geophysical inverse problems face a lot of issues to be solved, e.g., data noise problems: the general data records contain a lot of noise due to various factors in the excitation, propagation and ...

Abstract: Most modern imaging systems incorporate a computational pipeline to infer the image of interest from acquired measurements. The Bayesian approach to solve such ill-posed inverse problems ...

Dynamical systems have been used to model the paroxysmal nature of seizures in epilepsy. In parallel, seizures have been discovered to occur with cyclical periodicity in epilepsy, occurring at ...

The identification of synthetic routes that end with the desired product is considered an inherently time-consuming process that is largely dependent on expert knowledge regarding a limited proportion ...