A deep learning approach to the inversion of borehole resistivity measurements M Shahriari, D Pardo, A Picón, A Galdran, J Del Ser, C Torres-Verdín Computational Geosciences 24, 971-994, 2020 | 64 | 2020 |
Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements M Shahriari, D Pardo, JA Rivera, C Torres-Verdín, A Picon, J Del Ser, ... International Journal for Numerical Methods in Engineering, 2020 | 42 | 2020 |
A deep neural network as surrogate model for forward simulation of borehole resistivity measurements M Shahriari, D Pardo, B Moser, F Sobieczky Procedia Manufacturing 42, 235-238, 2020 | 36 | 2020 |
Modeling extra-deep EM logs using a deep neural network S Alyaev, M Shahriari, D Pardo, AJ Omella, D Larsen, N Jahani, E Suter GEOPHYSICS 86, E269-E281, 2021 | 32 | 2021 |
A numerical 1.5 D method for the rapid simulation of geophysical resistivity measurements M Shahriari, S Rojas, D Pardo, A Rodríguez-Rozas, SA Bakr, VM Calo, ... Geosciences 8 (6), 225, 2018 | 25 | 2018 |
How do deep-learning framework versions affect the reproducibility of neural network models? M Shahriari, R Ramler, L Fischer Machine Learning and Knowledge Extraction 4 (4), 888-911, 2022 | 7 | 2022 |
Borehole resistivity simulations of oil-water transition zones with a 1.5 D numerical solver M Shahriari, D Pardo Computational Geosciences 24, 1285-1299, 2020 | 6 | 2020 |
A deep learning approach to design a borehole instrument for geosteering M Shahriari, A Hazra, D Pardo Geophysics 87 (2), D83-D90, 2022 | 5 | 2022 |
Neural network architecture optimization using automated machine learning for borehole resistivity measurements M Shahriari, D Pardo, S Kargaran, T Teijeiro Geophysical Journal International 234 (3), 2487-2500, 2023 | 3 | 2023 |
Numerical modeling of magneto‐hydrodynamics flows using reproducing kernel particle method M Tatari, M Shahriari, M Raoofi International Journal of Numerical Modelling: Electronic Networks, Devices …, 2016 | 3 | 2016 |
A scoring algorithm for abnormal traveller behaviour in border crossing areas S Vora, M Shahriari, SCA Thomopoulos, L Fischer, T Hoch Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies …, 2020 | 2 | 2020 |
Requirements for Anomaly Detection Techniques for Microservices M Steidl, M Gattringer, M Felderer, R Ramler, M Shahriari International Conference on Product-Focused Software Process Improvement, 37-52, 2022 | 1 | 2022 |
A data transformation for the estimation of decay types of multivariate distributions F Sobieczky, M Shahriari, B Freudenthaler Procedia Manufacturing 42, 524-527, 2020 | 1 | 2020 |
Adjoint-based formulation for computing derivatives with respect to bed boundary positions in resistivity geophysics T Chaumont-Frelet, M Shahriari, D Pardo Computational Geosciences 23, 583-594, 2019 | 1 | 2019 |
Design of borehole resistivity measurement acquisition systems using deep learning M Shahriari, A Hazra, D Pardo https://arxiv.org/abs/2101.05623, 2021 | | 2021 |
Fast one-dimensional finite element approximation of geophysical measurements M Shahriari Shourabi | | 2018 |
Fast one-dimensional finite element approximation of geophysical measurements M Shahriari | | 2018 |
Geosteering using Deep Learning M Shahriari, D Pardo, JA Rivera | | |