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20162024
most citedBayesian Federated Learning: A Survey

7 citations · 21 across the 9 of their papers we have counts for

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Showing cs.LGShow all

5 papers · 1 filter

cs.LG2023

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…

cs.LG2023

Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management

Somya Sharma Chatterjee, Kelly Lindsay, Neel Chatterjee +6

In recent years, the increasing threat of devastating wildfires has underscored the need for effective prescribed fire management. Process-based computer simulations have tradition…

cs.LG2023

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…

cs.LG20237 cited

Bayesian Federated Learning: A Survey

Longbing Cao, Hui Chen, Xuhui Fan +3

Federated learning (FL) demonstrates its advantages in integrating distributed infrastructure, communication, computing and learning in a privacy-preserving manner. However, the ro…

cs.LG20236 cited

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…