Jordan S. Read
Orcid: 0000-0002-3888-6631
According to our database1,
Jordan S. Read
authored at least 21 papers
between 2011 and 2023.
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Bibliography
2023
Physics-guided machine learning from simulated data with different physical parameters.
Knowl. Inf. Syst., 2023
2022
Invertibility aware Integration of Static and Time-series data: An application to Lake Temperature Modeling.
Proceedings of the 2022 SIAM International Conference on Data Mining, 2022
2021
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles.
Trans. Data Sci., 2021
Environ. Model. Softw., 2021
Physics-Guided Recurrent Graph Model for Predicting Flow and Temperature in River Networks.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021
Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021
Physics-Guided Machine Learning from Simulation Data: An Application in Modeling Lake and River Systems.
Proceedings of the IEEE International Conference on Data Mining, 2021
Proceedings of the IEEE International Conference on Data Mining, 2021
2020
Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning.
CoRR, 2020
Physics-Guided Recurrent Graph Networks for Predicting Flow and Temperature in River Networks.
CoRR, 2020
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020
Process Guided Deep Learning for Modeling Physical Systems: An Application in Lake Temperature Modeling.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
2019
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019
2018
A multi-lake comparative analysis of the General Lake Model (GLM): Stress-testing across a global observatory network.
Environ. Model. Softw., 2018
Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes.
CoRR, 2018
2017
CoRR, 2017
2016
sbtools: A Package Connecting R to Cloud-based Data for Collaborative Online Research.
R J., 2016
2015
Environ. Model. Softw., 2015
Supporting Open Collaboration in Science Through Explicit and Linked Semantic Description of Processes.
Proceedings of the Semantic Web. Latest Advances and New Domains, 2015
2012
Time-scale dependence in numerical simulations: Assessment of physical, chemical, and biological predictions in a stratified lake at temporal scales of hours to months.
Environ. Model. Softw., 2012
2011
Derivation of lake mixing and stratification indices from high-resolution lake buoy data.
Environ. Model. Softw., 2011