1 citations · 2 across the 2 of their papers we have counts for
4 papers · 1 filter
Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning
Jared D. Willard, Jordan S. Read, Alison P. Appling +3
Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitor…
Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks
Xiaowei Jia, Beiyu Lin, Jacob Zwart +4
Effective training of advanced ML models requires large amounts of labeled data, which is often scarce in scientific problems given the substantial human labor and material cost to…
Physics-Guided Recurrent Graph Networks for Predicting Flow and Temperature in River Networks
Xiaowei Jia, Jacob Zwart, Jeffrey Sadler +8
This paper proposes a physics-guided machine learning approach that combines advanced machine learning models and physics-based models to improve the prediction of water flow and t…
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles
Xiaowei Jia, Jared Willard, Anuj Karpatne +4
Physics-based models of dynamical systems are often used to study engineering and environmental systems. Despite their extensive use, these models have several well-known limitatio…