2 citations · 2 across the 4 of their papers we have counts for
4 papers · 1 filter
Hierarchically Disentangled Recurrent Network for Factorizing System Dynamics of Multi-scale Systems: An application on Hydrological Systems
Rahul Ghosh, Arvind Renganathan, Zac McEachran +6
We present a framework for modeling multi-scale processes, and study its performance in the context of streamflow forecasting in hydrology. Specifically, we propose a novel hierarc…
Uncertainty Quantification in Inverse Models in Hydrology
Somya Sharma Chatterjee, Rahul Ghosh, Arvind Renganathan +5
In hydrology, modeling streamflow remains a challenging task due to the limited availability of basin characteristics information such as soil geology and geomorphology. These char…
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…
Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology
Rahul Ghosh, Arvind Renganathan, Kshitij Tayal +6
Machine Learning is beginning to provide state-of-the-art performance in a range of environmental applications such as streamflow prediction in a hydrologic basin. However, buildin…