1 citations · 2 across the 7 of their papers we have counts for
6 papers · 1 filter
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…
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems
Arvind Renganathan, Rahul Ghosh, Ankush Khandelwal +1
We introduce TAM-RL (Task Aware Modulation using Representation Learning), a novel multimodal meta-learning framework for few-shot learning in heterogeneous systems, designed for s…
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…
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…
Discovery of Shifting Patterns in Sequence Classification
Xiaowei Jia, Ankush Khandelwal, Anuj Karpatne +1
In this paper, we investigate the multi-variate sequence classification problem from a multi-instance learning perspective. Real-world sequential data commonly show discriminative…
ORBIT: Ordering Based Information Transfer Across Space and Time for Global Surface Water Monitoring
Ankush Khandelwal, Anuj Karpatne, Vipin Kumar
Many earth science applications require data at both high spatial and temporal resolution for effective monitoring of various ecosystem resources. Due to practical limitations in s…