The following pages link to Stanley P Mordensky (Q48139):
Displayed 11 items.
- What did they just say? Building a Rosetta stone for geoscience and machine learning (Q150736) (← links)
- Detrending Great Basin elevation to identify structural patterns for identifying geothermal favorability (Q255077) (← links)
- When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates (Q255821) (← links)
- Don’t Let Negatives Hold You Back: Accounting for Underlying Physics and Natural Distributions of Hydrothermal Systems When Selecting Negative Training Sites Leads to Better Machine Learning Predictions (Q276858) (← links)
- Predicting geothermal favorability in the western United States by using machine learning: Addressing challenges and developing solutions (Q292911) (← links)
- Predicting large hydrothermal systems (Q299337) (← links)
- New maps of conductive heat flow in the Great Basin, USA: Separating conductive and convective influences (Q314384) (← links)
- Cursed? Why one does not simply add new data sets to supervised geothermal machine learning models (Q314495) (← links)
- Maps of elevation trend and detrended elevation for the Great Basin, USA (Q320716) (← links)
- Heat flow maps and supporting data for the Great Basin, USA (Q324667) (← links)
- Geothermal resource favorability: select features and predictions for the western United States curated for DOI 10.1016/j.geothermics.2023.102662 (Q324682) (← links)