| Linear inverse Gaussian theory and geostatistics TM Hansen, AG Journel, A Tarantola, K Mosegaard Geophysics 71 (6), R101, 2006 | 191 | 2006 |
| Inverse problems with non-trivial priors: Efficient solution through Sequential Gibbs Sampling TM Hansen, KS Cordua, K Mosegaard Computational Geosciences, 1-19, 2012 | 148 | 2012 |
| Identifying unsaturated hydraulic parameters using an integrated data fusion approach on cross‐borehole geophysical data MC Looms, A Binley, KH Jensen, L Nielsen, TM Hansen Vadose Zone Journal 7 (1), 238-248, 2008 | 132 | 2008 |
| Monte Carlo full-waveform inversion of crosshole GPR data using multiple-point geostatistical a priori information KS Cordua, TM Hansen, K Mosegaard Geophysics 77 (2), H19-H31, 2012 | 111 | 2012 |
| SIPPI: A Matlab toolbox for sampling the solution to inverse problems with complex prior information: Part 2—Application to crosshole GPR tomography TM Hansen, KS Cordua, MC Looms, K Mosegaard Computers & Geosciences 52, 481-492, 2013 | 91 | 2013 |
| Accounting for imperfect forward modeling in geophysical inverse problems—exemplified for crosshole tomography TM Hansen, KS Cordua, BH Jacobsen, K Mosegaard Geophysics 79 (3), H1-H21, 2014 | 88 | 2014 |
| Gravity inversion predicts the nature of the Amundsen Basin and its continental borderlands near Greenland A Døssing, TM Hansen, AV Olesen, JR Hopper, T Funck Earth and Planetary Science Letters 408, 132-145, 2014 | 73 | 2014 |
| An unsupervised deep-learning method for porosity estimation based on poststack seismic data R Feng, T Mejer Hansen, D Grana, N Balling Geophysics 85 (6), M97-M105, 2020 | 72 | 2020 |
| Efficient Monte Carlo sampling of inverse problems using a neural network-based forward—Applied to GPR crosshole traveltime inversion TM Hansen, KS Cordua Geophysical Journal International 211 (3), 1524-1533, 2017 | 63 | 2017 |
| VISIM: Sequential simulation for linear inverse problems TM Hansen, K Mosegaard Computers & Geosciences 34 (1), 53-76, 2008 | 63 | 2008 |
| Bayesian convolutional neural networks for seismic facies classification R Feng, N Balling, D Grana, JS Dramsch, TM Hansen IEEE transactions on geoscience and remote sensing 59 (10), 8933-8940, 2021 | 58 | 2021 |
| Multiple-point statistical simulation for hydrogeological models: 3-D training image development and conditioning strategies AS Høyer, G Vignoli, TM Hansen, LT Vu, DA Keefer, F Jørgensen Hydrology and Earth System Sciences 21 (12), 6069-6089, 2017 | 56 | 2017 |
| Monte Carlo reservoir analysis combining seismic reflection data and informed priors A Zunino, K Mosegaard, K Lange, Y Melnikova, T Mejer Hansen Geophysics 80 (1), R31-R41, 2015 | 51 | 2015 |
| Using geostatistics to describe complex a priori information for inverse problems TM Hansen, K Mosegaard, KS Cordua VIII International Geostatistics Congress 1, 329-338, 2008 | 44 | 2008 |
| Attribute-guided well-log interpolation applied to low-frequency impedance estimation TM Hansen, K Mosegaard, R Pedersen-Tatalovic, A Uldall, NL Jacobsen Geophysics 73 (6), R83, 2008 | 41 | 2008 |
| A frequency matching method: solving inverse problems by use of geologically realistic prior information K Lange, J Frydendall, KS Cordua, TM Hansen, Y Melnikova, ... Mathematical geosciences 44, 783-803, 2012 | 37 | 2012 |
| MPSLIB: A C++ class for sequential simulation of multiple-point statistical models TM Hansen, LT Vu, T Bach SoftwareX 5, 127-133, 2016 | 36 | 2016 |
| Multiple point statistical simulation using uncertain (soft) conditional data TM Hansen, K Mosegaard, KS Cordua Computers & geosciences 114, 1-10, 2018 | 35 | 2018 |
| Probabilistic integration of geo‐information TM Hansen, KS Cordua, A Zunino, K Mosegaard Integrated imaging of the earth: Theory and applications, 93-116, 2016 | 35 | 2016 |
| Event-based low-frequency impedance modeling using well logs and seismic attributes R Pedersen-Tatalovic, A Uldall, NL Jacobsen, TM Hansen, K Mosegaard The Leading Edge 27 (5), 592-603, 2008 | 35 | 2008 |
Klaus MosegaardProfessor of Computational and Solid Earth Geophysics, University of Copenhagen在 nbi.ku.dk 的电子邮件经过验证
