Pages that link to "Item:Q50426"
From geokb
The following pages link to Jacob Zwart (Q50426):
Displayed 34 items.
- Graph-based reinforcement learning for active learning in real time: An application in modeling river networks (Q146037) (← links)
- Cross-scale interactions dictate regional lake carbon flux and productivity response to future climate (Q149334) (← 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)
- Physics-guided recurrent neural networks for predicting lake water temperature (Q150549) (← links)
- Virtual summit: Incorporating data science and open science in aquatic research (Q253748) (← 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)
- Evaluation of metrics and thresholds for use in national-scale river harmful algal bloom assessments (Q256651) (← links)
- The AEMON-J “Hacking Limnology” workshop series & virtual summit: Incorporating data science and open science in aquatic research (Q257189) (← links)
- Partial differential equation driven dynamic graph networks for predicting stream water temperature (Q258651) (← links)
- Using near-term forecasts and uncertainty partitioning to inform prediction of oligotrophic lake cyanobacterial density (Q260695) (← links)
- Response of lake metabolism to catchment inputs inferred using high-frequency lake and stream data from across the northern hemisphere (Q261699) (← links)
- Estimating pelagic primary production in lakes: Comparison of 14C incubation and free-water O2 approaches (Q262906) (← links)
- Improving estimates and forecasts of lake carbon dynamics using data assimilation (Q271513) (← links)
- Physics-guided machine learning from simulation data: An application in modeling lake and river systems (Q273872) (← links)
- National-scale remotely sensed lake trophic state from 1984 through 2020 (Q276733) (← links)
- A synergistic future for AI and ecology (Q280314) (← 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 graph meta learning for predicting water temperature and streamflow in stream networks (Q285953) (← 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)
- Physics-guided machine learning for scientific discovery: An application in simulating lake temperature profiles (Q295199) (← links)
- Measurement and variability of lake metabolism (Q297765) (← links)
- Projected changes of regional lake hydrologic characteristics in response to 21st century climate change (Q300417) (← links)
- Fair graph learning using constraint-aware priority adjustment and graph masking in river networks (Q304054) (← links)
- Can machine learning accelerate process understanding and decision-relevant predictions of river water quality? (Q307225) (← links)
- Process-guided deep learning predictions of lake water temperature (Q308420) (← links)
- Data release: early warning indicators for harmful algal bloom assessments in the Illinois River, 2013 - 2020 (Q319047) (← links)
- Data to support water quality modeling efforts in the Delaware River Basin (Q319838) (← links)
- Predictions and supporting data for network-wide 7-day ahead forecasts of water temperature in the Delaware River Basin (Q323561) (← links)
- Data to support near-term forecasts of stream temperature using process-guided deep learning and data assimilation (Q325055) (← links)
- Multi-task Deep Learning for Water Temperature and Streamflow Prediction (ver. 1.1, June 2022) (Q326264) (← links)
- PRMS-SNTemp-EnKF - Precipitation Runoff Modeling System, Stream Network Temperature module, Ensemble Kalman Filter data assimilation framework (Q336730) (← links)
