29 citations · 100 across the 18 of their papers we have counts for
18 papers
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…
Towards Knowledge Guided Pretraining Approaches for Multimodal Foundation Models: Applications in Remote Sensing
Praveen Ravirathinam, Ajitesh Parthasarathy, Ankush Khandelwal +2
Self-supervised learning has emerged as a powerful paradigm for pretraining foundation models using large-scale data. Existing pretraining approaches predominantly rely on masked r…
Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach
Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal +3
Accurate and timely crop mapping is essential for yield estimation, insurance claims, and conservation efforts. Over the years, many successful machine learning models for crop map…
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…
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…