5 citations · 5 across the 2 of their papers we have counts for
2 papers
cs.LG2022
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…
cs.LG2021★ 5 cited
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…