Results 51 to 60 of about 846,274 (324)
Ensemble Kalman filter for neural network based one-shot inversion
, 2020 We study the use of novel techniques arising in machine learning for inverse problems. Our approach replaces the complex forward model by a neural network, which is trained simultaneously in a one-shot sense when estimating the unknown parameters from ...
Guth, Philipp A. +2 more
core +1 more source
Non-Gaussian bivariate modelling with application to atmospheric trace-gas inversion [PDF]
, 2016 Atmospheric trace-gas inversion is the procedure by which the sources and sinks of a trace gas are identified from observations of its mole fraction at isolated locations in space and time. This is inherently a spatio-temporal bivariate inversion problem,
Cressie, Noel +2 more
core +5 more sources
Journal of Marine Science and Engineering, 2019 The key to model-based Bayesian geoacoustic inversion is to solve the posterior probability distributions (PPDs) of parameters. In order to obtain PPDs more efficiently and accurately, the state-of-the-art Markov chain Monte Carlo (MCMC) method, multiple-
Bo Zou +5 more
doaj +1 more source
Inferences of mantle viscosity based on ice age data sets: Radial structure [PDF]
, 2016 We perform joint nonlinear inversions of glacial isostatic adjustment (GIA) data, including the following: postglacial decay times in Canada and Scandinavia, the Fennoscandian relaxation spectrum (FRS), late-Holocene differential sea level (DSL ...
core +2 more sources
Bayesian Multitask Inverse Reinforcement Learning [PDF]
, 2012 We generalise the problem of inverse reinforcement learning to multiple tasks, from multiple demonstrations. Each one may represent one expert trying to solve a different task, or as different experts trying to solve the same task. Our main contribution is to formalise the problem as statistical preference elicitation, via a number of structured priors,
Dimitrakakis C., Rothkopf C.A.
openaire +2 more sources
Bayesian Approach to Inverse Quantum Statistics [PDF]
Physical Review Letters, 2000 A nonparametric Bayesian approach is developed to determine quantum potentials from empirical data for quantum systems at finite temperature. The approach combines the likelihood model of quantum mechanics with a priori information over potentials implemented in form of stochastic processes.
Lemm, J. C., Uhlig, J., Weiguny, A.
openaire +3 more sources
Frontiers in Marine Science, 2023 Underwater acoustic technology is essential for ocean observation, exploration and exploitation, and its development is based on an accurate predication of underwater acoustic wave propagation.
Hanhao Zhu +9 more
doaj +1 more source
Evaluation of mineralogy per geological layers by Approximate Bayesian Computation
, 2019 We propose a new methodology to perform mineralogic inversion from wellbore logs based on a Bayesian linear regression model. Our method essentially relies on three steps.
Bruned, Vianney +3 more
core +3 more sources
Bayesian Inversion of Frequency-Domain Airborne EM Data With Spatial Correlation Prior Information
IEEE Transactions on Geoscience and Remote SensingThe Bayesian inversion of electromagnetic data can obtain key information on the uncertainty of subsurface resistivity. However, due to its high computational cost, Bayesian inversion is largely limited to 1-D resistivity models.
Jianmei Zhou +7 more
semanticscholar +1 more source
Bayesian Inverse Quantum Theory [PDF]
Few-Body Systems, 2000 LaTex, 32 pages, 19 ...
Lemm, J. C., Uhlig, J.
openaire +2 more sources