Pages that link to "Item:Q138487"
From geokb
The following pages link to Jeffrey Sadler (Q138487):
Displayed 15 items.
- Graph-based reinforcement learning for active learning in real time: An application in modeling river networks (Q146037) (← links)
- Near-term forecasts of stream temperature using deep learning and data assimilation in support of management decisions (Q150101) (← links)
- Machine learning for understanding inland water quantity, quality, and ecology (Q150299) (← links)
- Multi-task deep learning of daily streamflow and water temperature (Q253766) (← links)
- Evaluating deep learning architecture and data assimilation for improving water temperature forecasts at unmonitored locations (Q256026) (← links)
- Stream temperature prediction in a shifting environment: The influence of deep learning architecture (Q257873) (← links)
- Partial differential equation driven dynamic graph networks for predicting stream water temperature (Q258651) (← links)
- Physics-guided machine learning from simulation data: An application in modeling lake and river systems (Q273872) (← links)
- Using machine learning to develop a predictive understanding of the impacts of extreme water cycle perturbations on river water quality (Q281781) (← links)
- Physics-guided recurrent graph model for predicting flow and temperature in river networks (Q287501) (← links)
- Heterogeneous stream-reservoir graph networks with data assimilation (Q292369) (← links)
- Can machine learning accelerate process understanding and decision-relevant predictions of river water quality? (Q307225) (← links)
- Model Code, Outputs, and Supporting Data for Approaches to Process-Guided Deep Learning for Groundwater-Influenced Stream Temperature Predictions (Q319812) (← links)
- Examining the influence of deep learning architecture on generalizability for predicting stream temperature in the Delaware River Basin (Q324344) (← links)
- Multi-task Deep Learning for Water Temperature and Streamflow Prediction (ver. 1.1, June 2022) (Q326264) (← links)
