Pinned Repositories
Tuning-Dropout-for-Uncertainty-Models
Example code for "Tuning machine learning dropout for subsurface uncertainty model accuracy" https://doi.org/10.1016/j.petrol.2021.108975
Robust-Spatial-Uncertainty-Modeling-Workflow-Surrogate-Flow-Model
This repository contains a new and general workflow to generate accurate and precise machine learning-based surrogate flow models. https://doi.org/10.1016/j.petrol.2022.110244
UTuning
Uncertainty Tuning (UTuning) is a package that tunes hyperparameters based on the model goodness metric.
Datasets
hello-world
Images
Multi-horizon_well-performance_forecasting
Public repository for the publication Multi-horizon well performance forecasting with temporal fusion transformers. Authors: Eduardo Maldonado-Cruz, Michael J. Pyrcz
Properties_of_petroleum_fluids
Publication_figure_style
Python_numerical_demos
emaldonadocruz's Repositories
emaldonadocruz/Multi-horizon_well-performance_forecasting
Public repository for the publication Multi-horizon well performance forecasting with temporal fusion transformers. Authors: Eduardo Maldonado-Cruz, Michael J. Pyrcz
emaldonadocruz/Datasets
emaldonadocruz/Publication_figure_style
emaldonadocruz/UTuning
Uncertainty Tuning (UTuning) is a package that tunes hyperparameters based on the model goodness metric.
emaldonadocruz/Robust-Spatial-Uncertainty-Modeling-Workflow-Surrogate-Flow-Model
This repository contains a new and general workflow to generate accurate and precise machine learning-based surrogate flow models. https://doi.org/10.1016/j.petrol.2022.110244
emaldonadocruz/Python_numerical_demos
emaldonadocruz/Reservoir_engineering
emaldonadocruz/Properties_of_petroleum_fluids
emaldonadocruz/Images
emaldonadocruz/Tuning-Dropout-for-Uncertainty-Models
Example code for "Tuning machine learning dropout for subsurface uncertainty model accuracy" https://doi.org/10.1016/j.petrol.2021.108975
emaldonadocruz/hello-world