| Multiresolution neural networks for tracking seismic horizons from few training images B Peters, J Granek, E Haber Interpretation 7 (3), SE201-SE213, 2019 | 70 | 2019 |
| Neural networks for geophysicists and their application to seismic data interpretation B Peters, E Haber, J Granek The Leading Edge 38 (7), 534-540, 2019 | 52 | 2019 |
| Application of machine learning algorithms to mineral prospectivity mapping J Granek University of British Columbia, 2016 | 31 | 2016 |
| Data mining for real mining: A robust algorithm for prospectivity mapping with uncertainties J Granek, E Haber Proceedings of the 2015 SIAM international conference on data mining, 145-153, 2015 | 23 | 2015 |
| An adaptive mesh method for electromagnetic inverse problems E Haber, D Oldenburg, C Schwarzbach, R Shekhtman, E Holtham, ... SEG International Exposition and Annual Meeting, SEG-2012-0828, 2012 | 18 | 2012 |
| Using machine learning to interpret 3D airborne electromagnetic inversions E Haber, J Fohring, M McMillan, J Granek ASEG Extended Abstracts 2019 (1), 1-4, 2019 | 9 | 2019 |
| Machine learning systems and methods for document matching EM Holtham, A Shafaei, J Granek US Patent App. 15/903,344, 2018 | 8 | 2018 |
| Advanced geoscience targeting via focused machine learning applied to the QUEST project dataset, British Columbia J Granek, E Haber Geoscience BC Summary of Activities 2011, 2016 | 7 | 2016 |
| 3D inversion of DC/IP data using adaptive OcTree meshes E Haber, D Oldenburg, R Shekhtman, J Granek, D Marchant, E Holtham SEG International Exposition and Annual Meeting, SEG-2012-1438, 2012 | 7 | 2012 |
| Computing geologically consistent models from geophysical data J Granek University of British Columbia, 2011 | 7 | 2011 |
| Multiresolution neural networks for tracking seismic horizons from few training images: Interpretation, 7 B Peters, J Granek, E Haber SE201–SE213, 2019 | 6 | 2019 |
| Orogenic gold prospectivity mapping using machine learning M McMillan, J Fohring, E Haber, J Granek ASEG Extended Abstracts 2019 (1), 1-4, 2019 | 5 | 2019 |
| Automatic classification of geologic units in seismic images using partially interpreted examples B Peters, J Granek, E Haber 81st EAGE Conference and Exhibition 2019 2019 (1), 1-5, 2019 | 5 | 2019 |
| Does shallow geological knowledge help neural-networks to predict deep units? B Peters, E Haber, J Granek SEG International Exposition and Annual Meeting, D033S038R002, 2019 | 2 | 2019 |
| Resource Management through Machine Learning J Granek, E Haber, E Holtham ASEG Extended Abstracts 2016 (1), 1-5, 2016 | 1 | 2016 |
| Sensor systems and methods for facility operation management JS Granek, EM Holtham US Patent App. 17/330,971, 2022 | | 2022 |
| Ultra High-resolution Imaging of Brachiopod Shells: Assessing Their Robustness as Paleo-environmental Indicators JS Granek Acadia University, 2009 | | 2009 |
| Advanced Geoscience Targeting via Focused Machine Learning J Granek, E Haber | | |
Eldad HaberProfessor of Mathematics and Geophysics UBCVerified email at eoas.ubc.ca
Eldad HaberProfessor of Mathematics and Geophysics UBCVerified email at eoas.ubc.ca