Shaoming Xu

According to our database, Shaoming Xu authored at least 10 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Hierarchical Conditional Multi-Task Learning for Streamflow Modeling.

Shaoming Xu, Arvind Renganathan, Ankush Khandelwal, Rahul Ghosh, Xiang Li, Licheng Liu, Kshitij Tayal, Peter Harrington, Xiaowei Jia, Zhenong Jin, John Nieber, Vipin Kumar

CoRR, 2024

Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling.

Jaideep Pathak, Yair Cohen, Piyush Garg, Peter Harrington, Noah D. Brenowitz, Dale R. Durran, Morteza Mardani, Arash Vahdat, Shaoming Xu, Karthik Kashinath, Michael S. Pritchard

CoRR, 2024

Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling.

Shaoming Xu, Ankush Khandelwal, Arvind Renganathan, Vipin Kumar

Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

2023

Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems.

Jared Willard, Xiaowei Jia, Shaoming Xu, Michael S. Steinbach, Vipin Kumar

ACM Comput. Surv., 2023

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

Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar

Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

2021

Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making.

Yolanda Gil, Daniel Garijo, Deborah Khider, Craig A. Knoblock, Varun Ratnakar, Maximiliano Osorio, Hernán Vargas, Minh Pham, Jay Pujara, Basel Shbita, Binh Vu, Yao-Yi Chiang, Dan Feldman, Yijun Lin, Hayley Song, Vipin Kumar, Ankush Khandelwal, Michael S. Steinbach, Kshitij Tayal, Shaoming Xu, Suzanne A. Pierce, Lissa Pearson, Daniel Hardesty-Lewis, Ewa Deelman, Rafael Ferreira da Silva, Rajiv Mayani, Armen R. Kemanian, Yuning Shi, Lorne Leonard, Scott D. Peckham, Maria Stoica, Kelly M. Cobourn, Zeya Zhang, Christopher J. Duffy, Lele Shu

ACM Trans. Interact. Intell. Syst., 2021

Physics-Guided Recurrent Graph Model for Predicting Flow and Temperature in River Networks.

Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Steven Markstrom, Jared Willard, Shaoming Xu, Michael S. Steinbach, Jordan S. Read, Vipin Kumar

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

2020

Physics Guided Machine Learning Methods for Hydrology.

Ankush Khandelwal, Shaoming Xu, Xiang Li, Xiaowei Jia, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar

CoRR, 2020

Physics-Guided Recurrent Graph Networks for Predicting Flow and Temperature in River Networks.

Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Steven Markstrom, Jared Willard, Shaoming Xu, Michael S. Steinbach, Jordan S. Read, Vipin Kumar

CoRR, 2020

Integrating Physics-Based Modeling with Machine Learning: A Survey.

Jared Willard, Xiaowei Jia, Shaoming Xu, Michael S. Steinbach, Vipin Kumar

CoRR, 2020