14 citations · 23 across the 3 of their papers we have counts for
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cs.LG2018
Langevin-gradient parallel tempering for Bayesian neural learning
Rohitash Chandra, Konark Jain, Ratneel V. Deo +1
Bayesian neural learning feature a rigorous approach to estimation and uncertainty quantification via the posterior distribution of weights that represent knowledge of the neural n…
physics.geo-ph2018★ 14 cited
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…