8 papers · 1 filter
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…
Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling
Kshitij Tayal, Arvind Renganathan, Rahul Ghosh +2
Accurate long-term predictions are the foundations for many machine learning applications and decision-making processes. However, building accurate long-term prediction models rema…
Entity Aware Modelling: A Survey
Rahul Ghosh, Haoyu Yang, Ankush Khandelwal +5
Personalized prediction of responses for individual entities caused by external drivers is vital across many disciplines. Recent machine learning (ML) advances have led to new stat…
Spatiotemporal Classification with limited labels using Constrained Clustering for large datasets
Praveen Ravirathinam, Rahul Ghosh, Ke Wang +5
Creating separable representations via representation learning and clustering is critical in analyzing large unstructured datasets with only a few labels. Separable representations…
Probabilistic Inverse Modeling: An Application in Hydrology
Somya Sharma, Rahul Ghosh, Arvind Renganathan +5
The astounding success of these methods has made it imperative to obtain more explainable and trustworthy estimates from these models. In hydrology, basin characteristics can be no…
Weakly Supervised Classification Using Group-Level Labels
Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia +1
In many applications, finding adequate labeled data to train predictive models is a major challenge. In this work, we propose methods to use group-level binary labels as weak super…