3 papers
cs.LG2026
PIER: Physics-Informed Environmental Retrieval for Time-Series Modeling
Shiyuan Luo, Runlong Yu, Chonghao Qiu +6
Accurate modeling of environmental systems is fundamental to scientific understanding and decision-making, yet remains challenging because observations are limited and physical dyn…
cs.LG2025
Learning to Retrieve for Environmental Knowledge Discovery: An Augmentation-Adaptive Self-Supervised Learning Framework
Shiyuan Luo, Runlong Yu, Chonghao Qiu +5
The discovery of environmental knowledge depends on labeled task-specific data, but is often constrained by the high cost of data collection. Existing machine learning approaches u…
cs.LG2025
Physics-Guided Foundation Model for Scientific Discovery: An Application to Aquatic Science
Runlong Yu, Chonghao Qiu, Robert Ladwig +3
Physics-guided machine learning (PGML) has become a prevalent approach in studying scientific systems due to its ability to integrate scientific theories for enhancing machine lear…