68 citations · 112 across the 7 of their papers we have counts for
7 papers
Hierarchical Conditional Multi-Task Learning for Streamflow Modeling
Shaoming Xu, Arvind Renganathan, Ankush Khandelwal +9
Streamflow, vital for water resource management, is governed by complex hydrological systems involving intermediate processes driven by meteorological forces. While deep learning m…
Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling
Jaideep Pathak, Yair Cohen, Piyush Garg +8
Storm-scale convection-allowing models (CAMs) are an important tool for predicting the evolution of thunderstorms and mesoscale convective systems that result in damaging extreme w…
Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling
Shaoming Xu, Ankush Khandelwal, Arvind Renganathan +1
Time series modeling, a crucial area in science, often encounters challenges when training Machine Learning (ML) models like Recurrent Neural Networks (RNNs) using the conventional…
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…
Physics Guided Machine Learning Methods for Hydrology
Ankush Khandelwal, Shaoming Xu, Xiang Li +5
Streamflow prediction is one of the key challenges in the field of hydrology due to the complex interplay between multiple non-linear physical mechanisms behind streamflow generati…
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…
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
Jared Willard, Xiaowei Jia, Shaoming Xu +2
There is a growing consensus that solutions to complex science and engineering problems require novel methodologies that are able to integrate traditional physics-based modeling ap…