3 papers
stat.ML2018
Surrogate-assisted Bayesian inversion for landscape and basin evolution models
Rohitash Chandra, Danial Azam, Arpit Kapoor +1
The complex and computationally expensive nature of landscape evolution models pose significant challenges in the inference and optimisation of unknown parameters. Bayesian inferen…
cs.CV2018
Computer vision-based framework for extracting geological lineaments from optical remote sensing data
Ehsan Farahbakhsh, Rohitash Chandra, Hugo K. H. Olierook +4
The extraction of geological lineaments from digital satellite data is a fundamental application in remote sensing. The location of geological lineaments such as faults and dykes a…
physics.geo-ph2018
Multi-core parallel tempering Bayeslands for basin and landscape evolution
Rohitash Chandra, R. Dietmar Müller, Danial Azam +4
The Bayesian paradigm is becoming an increasingly popular framework for estimation and uncertainty quantification of unknown parameters in geo-physical inversion problems. Badlands…