45 citations · 55 across the 15 of their papers we have counts for
16 papers
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…
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…
Mapping smallholder cashew plantations to inform sustainable tree crop expansion in Benin
Leikun Yin, Rahul Ghosh, Chenxi Lin +9
Cashews are grown by over 3 million smallholders in more than 40 countries worldwide as a principal source of income. As the third largest cashew producer in Africa, Benin has near…
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…
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…
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…
Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping
Rahul Ghosh, Xiaowei Jia, Chenxi Lin +2
Collecting large annotated datasets in Remote Sensing is often expensive and thus can become a major obstacle for training advanced machine learning models. Common techniques of ad…
CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels
Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia +3
Mapping and monitoring crops is a key step towards sustainable intensification of agriculture and addressing global food security. A dataset like ImageNet that revolutionized compu…
Attention-augmented Spatio-Temporal Segmentation for Land Cover Mapping
Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia +3
The availability of massive earth observing satellite data provide huge opportunities for land use and land cover mapping. However, such mapping effort is challenging due to the ex…
Land Cover Mapping in Limited Labels Scenario: A Survey
Rahul Ghosh, Xiaowei Jia, Vipin Kumar
Land cover mapping is essential for monitoring global environmental change and managing natural resources. Unfortunately, traditional classification models are plagued by limited t…
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data
Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia +2
Many real-world phenomena are observed at multiple resolutions. Predictive models designed to predict these phenomena typically consider different resolutions separately. This appr…