activity
20182025
most citedPredicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning

88 citations · 284 across the 10 of their papers we have counts for

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Showing cs.LGShow all

7 papers · 1 filter

cs.LG2025★ 1 cited

Foundation Models for Environmental Science: A Survey of Emerging Frontiers

Runlong Yu, Shengyu Chen, Yiqun Xie +3

Modeling environmental ecosystems is essential for effective resource management, sustainable development, and understanding complex ecological processes. However, traditional data…

cs.LG2024★ 2 cited

Evaluating Deep Learning Approaches for Predictions in Unmonitored Basins with Continental-scale Stream Temperature Models

Jared D. Willard, Fabio Ciulla, Helen Weierbach +2

The prediction of streamflows and other environmental variables in unmonitored basins is a grand challenge in hydrology. Recent machine learning (ML) models can harness vast datase…

cs.LG2023★ 29 cited

Time Series Predictions in Unmonitored Sites: A Survey of Machine Learning Techniques in Water Resources

Jared D. Willard, Charuleka Varadharajan, Xiaowei Jia +1

Prediction of dynamic environmental variables in unmonitored sites remains a long-standing challenge for water resources science. The majority of the world's freshwater resources h…

cs.LG2022

Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications

Shaoming Xu, Ankush Khandelwal, Xiang Li +9

In many environmental applications, recurrent neural networks (RNNs) are often used to model physical variables with long temporal dependencies. However, due to mini-batch training…

cs.LG2020★ 88 cited

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…

cs.LG2020★ 41 cited

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…

cs.LG2018★ 34 cited

Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes

Xiaowei Jia, Anuj Karpatne, Jared Willard +5

In this paper, we introduce a novel framework for combining scientific knowledge within physics-based models and recurrent neural networks to advance scientific discovery in many d…