| Machine learning and deep learning methods in mining operations: A data-driven SAG mill energy consumption prediction application S Avalos, W Kracht, JM Ortiz Mining, Metallurgy & Exploration 37 (4), 1197-1212, 2020 | 46 | 2020 |
| Recursive convolutional neural networks in a multiple-point statistics framework S Avalos, JM Ortiz Computers & geosciences 141, 104522, 2020 | 28 | 2020 |
| Geological modeling using a recursive convolutional neural networks approach S Avalos, JM Ortiz arXiv preprint arXiv:1904.12190, 2019 | 13 | 2019 |
| An LSTM approach for SAG mill operational relative-hardness prediction S Avalos, W Kracht, JM Ortiz Minerals 10 (9), 734, 2020 | 11 | 2020 |
| A guide for pit optimization with pseudoflow in python S Avalos, JM Ortiz Queen's University, 2020 | 6 | 2020 |
| Convolutional neural networks architecture: A tutorial S Avalos, JM Ortiz Queen's University, 2019 | 4 | 2019 |
| Uncertainty and value: optimising geometallurgical performance along the mining value chain JM Ortiz, S Avalos, AI Riquelme, O Leuangthong, N Madani, M Frenzel Elements 19 (6), 377-383, 2023 | 3 | 2023 |
| Multivariate Geostatistical Simulation and Deep Q-Learning to optimize mining decisions S Avalos, JM Ortiz Mathematical Geosciences 55 (5), 673-692, 2023 | 3 | 2023 |
| Fundamentals of deep Q-Learning S Avalos, JM Ortiz Predictive Geometallurgy and Geostatistics Lab, Paper 2021-02, 14-21, 2021 | 2 | 2021 |
| Multiple-point statistics: tools and methods S Avalos, JM Ortiz Queen's University, 2020 | 2 | 2020 |
| Predictive Geometallurgy and Geostatistics Lab-Annual Report 2022 JM Ortiz, S Avalos, D Casson, S Kheirparast, P Larrondo, T Li, A Marino, ... Predictive Geometallurgy and Geostatistics Lab, Queen’s University, 2019 | 1 | 2019 |
| Predictive Geometallurgy and Geostatistics Lab-Annual Report 2019 S Avalos, M Bolgkoranou, SI Cevik, W Kracht, W Midkiff, GR Olivo, ... Predictive Geometallurgy and Geostatistics Lab, 2019 | 1 | 2019 |
| Using LSTM and GRU to predict SAG mill energy consumption S Avalos, W Kracht, JM Ortiz Queen's University, 2019 | 1 | 2019 |
| Simulación multipuntos utilizando el algoritmo filtersim: incorporación de derivadas en la media local SA Ávalos Sotomayor | 1 | 2014 |
| Spatial Multivariate Morphing Transformation S Avalos, JM Ortiz Mathematical Geosciences 55 (6), 735-771, 2023 | | 2023 |
| Geostatistics Toronto 2021 S Avalos, JM Ortiz, RM Srivastava Mathematical Geosciences 55 (5), 607-608, 2023 | | 2023 |
| Fluid inclusions technique for porphyry deposit exploration: The Rosario porphyry Cu-Mo deposit S Avalos, N Avalos EarthArXiv, 2023 | | 2023 |
| Geostatistics Toronto 2021: Quantitative Geology and Geostatistics SA Avalos Sotomayor, JM Ortiz, RM Srivastava Springer Nature, 2023 | | 2023 |
| Advanced predictive methods applied to geometallurgical modelling S Avalos Sotomayor | | 2021 |
| Advanced Predictive Methods Applied to Geometallurgical Modelling SAA Sotomayor Queen's University (Canada), 2021 | | 2021 |
Julián OrtizCamborne School of Mines, University of ExeterVerified email at exeter.ac.uk