1 citations · 1 across the 4 of their papers we have counts for
4 papers
GraMeR: Graph Meta Reinforcement Learning for Multi-Objective Influence Maximization
Sai Munikoti, Balasubramaniam Natarajan, Mahantesh Halappanavar
Influence maximization (IM) is a combinatorial problem of identifying a subset of nodes called the seed nodes in a network (graph), which when activated, provide a maximal spread o…
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…
An Information Theoretic approach to identify Dominant Voltage Influencers for Unbalanced Distribution Systems
Sai Munikoti, Mohammad Abujubbeh, Kumarsinh Jhala +1
Smart distribution grid with multiple renewable energy sources can experience random voltage fluctuations due to variable generation, which may result in voltage violations. Tradit…
Probabilistic Voltage Sensitivity based Preemptive Voltage Monitoring in Unbalanced Distribution Networks
Mohammad Abujubbeh, Sai Munikoti, Balasubramaniam Natarajan
With increasing penetration of renewable energy and active consumers, control and management of power distribution networks has become challenging. Renewable energy sources can cau…