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 001 (CoRR, 2020)

Knowledge-guided Self-supervised Learning for estimating River-Basin Characteristics. - Rahul Ghosh; Arvind Renganathan; Ankush Khandelwal; Xiaowei Jia; Xiang Li; John Nieber; Christopher J. Duffy; Vipin Kumar 001 (CoRR, 2021)

Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology. - Rahul Ghosh; Arvind Renganathan; Kshitij Tayal; Xiang Li; Ankush Khandelwal; Xiaowei Jia; Christopher J. Duffy; John Nieber; Vipin Kumar 001 (KDD, 2022)

Probabilistic Inverse Modeling: An Application in Hydrology. - Somya Sharma; Rahul Ghosh; Arvind Renganathan; Xiang Li; Snigdhansu Chatterjee; John Nieber; Christopher J. Duffy; Vipin Kumar 001 (SDM, 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 001 (SDM, 2023)

Uncertainty Quantification in Inverse Models in Hydrology. - Somya Sharma Chatterjee; Rahul Ghosh; Arvind Renganathan; Xiang Li; Snigdhansu Chatterjee; John Nieber; Christopher J. Duffy; Vipin Kumar 001 (CoRR, 2023)

Hierarchically Disentangled Recurrent Network for Factorizing System Dynamics of Multi-scale Systems. - Rahul Ghosh; Zac McEachran; Arvind Renganathan; Kelly Lindsay; Somya Sharma Chatterjee; Michael S. Steinbach; John Nieber; Christopher J. Duffy; Vipin Kumar 001 (CoRR, 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 001 (CoRR, 2024)