7 citations · 13 across the 5 of their papers we have counts for
5 papers
Active Foundational Models for Fault Diagnosis of Electrical Motors
Sriram Anbalagan, Sai Shashank GP, Deepesh Agarwal +2
Fault detection and diagnosis of electrical motors are of utmost importance in ensuring the safe and reliable operation of several industrial systems. Detection and diagnosis of fa…
Foundational Models for Fault Diagnosis of Electrical Motors
Sriram Anbalagan, Deepesh Agarwal, Balasubramaniam Natarajan +1
A majority of recent advancements related to the fault diagnosis of electrical motors are based on the assumption that training and testing data are drawn from the same distributio…
Challenges and Opportunities in Deep Reinforcement Learning with Graph Neural Networks: A Comprehensive review of Algorithms and Applications
Sai Munikoti, Deepesh Agarwal, Laya Das +2
Deep reinforcement learning (DRL) has empowered a variety of artificial intelligence fields, including pattern recognition, robotics, recommendation-systems, and gaming. Similarly,…
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks
Sai Munikoti, Deepesh Agarwal, Laya Das +1
Graph Neural Networks (GNN) provide a powerful framework that elegantly integrates Graph theory with Machine learning for modeling and analysis of networked data. We consider the p…
Addressing practical challenges in Active Learning via a hybrid query strategy
Deepesh Agarwal, Pravesh Srivastava, Sergio Martin-del-Campo +2
Active Learning (AL) is a powerful tool to address modern machine learning problems with significantly fewer labeled training instances. However, implementation of traditional AL m…