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One of the major goals for astronomy in the next decades is the remote search for biosignatures (i.e., the spectroscopic evidence of biological activity) in exoplanets. Here we adopt a Bayesian statistical framework to discuss the implications of such futu ...
The increasing integration of intermittent renewable generation, especially at the distribution level, necessitates advanced planning and optimisation methodologies contingent on the knowledge of the admittance matrix, capturing the topology and line param ...
Bayesian statistics is concerned with the integration of new information obtained through observations with prior knowledge, and accordingly, is often related to information theory (Jospin 2022). Recursive Bayesian estimation methods, such as Kalman Filter ...
The H0LiCOWcollaboration inferred via strong gravitational lensing time delays a Hubble constant value of H0 = 73 :3+1:7 1:8 km s 1 Mpc 1, describing deflector mass density profiles by either a power-law or stars (constant mass-to-light ratio) plus standar ...
The application of Bayesian modeling techniques is increasingly common in neuroscience due to the coherent and principled way in which the paradigm deals with uncertainty. The Bayesian framework is particularly valuable in the context of complex, ill-posed ...
Classic image-restoration algorithms use a variety of priors, either implicitly or explicitly. Their priors are hand-designed and their corresponding weights are heuristically assigned. Hence, deep learning methods often produce superior image restoration ...
Accurate spatiotemporal modeling of conditions leading to moderate and large wildfires provides better understanding of mechanisms driving fire-prone ecosystems and improves risk management. Here, we develop a joint model for the occurrence intensity and t ...
Back analysis can provide engineers with important information for better decision-making. Over the years, research on back analysis has focused mainly on optimisation techniques, while comparative studies of data-interpretation methodologies have seldom b ...
The largest source of systematic errors in the time-delay cosmography method likely arises from the lens model mass distribution, where an inaccurate choice of model could in principle bias the value of H-0. A Bayesian hierarchical framework has been propo ...
We study the computations that Bayesian agents undertake when exchanging opinions over a network. The agents act repeatedly on their private information and take myopic actions that maximize their expected utility according to a fully rational posterior be ...
