| Improving predictive models for rate of penetration in real drilling operations through transfer learning FJ Pacis, A Ambrus, S Alyaev, R Khosravanian, TG Kristiansen, ... Journal of Computational Science 72, 102100, 2023 | 5 | 2023 |
| Transfer Learning Approach to Prediction of Rate of Penetration in Drilling FJ Pacis, S Alyaev, A Ambrus, T Wiktorski International Conference on Computational Science, 358-371, 2022 | 3 | 2022 |
| Rate of Penetration Prediction Using Quantile Regression Deep Neural Networks A Ambrus, S Alyaev, N Jahani, FJ Pacis, T Wiktorski International Conference on Offshore Mechanics and Arctic Engineering 85956 …, 2022 | 3 | 2022 |
| An End-To-End Machine Learning Project for Detection of Stuck Pipe Symptoms During Tripping Operations FJ Pacis uis, 2021 | 2 | 2021 |
| Exploration of Strategies to Improve Continual Learning From Irregular Sequential Drilling Data FJ Pacis, T Wiktorski, A Ambrus, S Alyaev International Conference on Offshore Mechanics and Arctic Engineering 86915 …, 2023 | 1 | 2023 |
| Enhancing Information Retrieval in the Drilling Domain: Zero-Shot Learning with Large Language Models for Question-Answering FJ Pacis, S Alyaev, G Pelfrene, T Wiktorski SPE/IADC Drilling Conference and Exhibition, D011S002R004, 2024 | | 2024 |
