62 citations · 178 across the 15 of their papers we have counts for
15 papers
GNN-Based Candidate Node Predictor for Influence Maximization in Temporal Graphs
Priyanka Gautam, Balasubramaniam Natarajan, Sai Munikoti +2
In an age where information spreads rapidly across social media, effectively identifying influential nodes in dynamic networks is critical. Traditional influence maximization strat…
A General Framework for Uncertainty Quantification via Neural SDE-RNN
Shweta Dahale, Sai Munikoti, Balasubramaniam Natarajan
Uncertainty quantification is a critical yet unsolved challenge for deep learning, especially for the time series imputation with irregularly sampled measurements. To tackle this p…
There is more to graphs than meets the eye: Learning universal features with self-supervision
Laya Das, Sai Munikoti, Nrushad Joshi +1
We study the problem of learning features through self-supervision that are generalisable to multiple graphs. State-of-the-art graph self-supervision restricts training to only one…
Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids
Shweta Dahale, Sai Munikoti, Balasubramaniam Natarajan +1
Under a smart grid paradigm, there has been an increase in sensor installations to enhance situational awareness. The measurements from these sensors can be leveraged for real-time…
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,…
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…
Bayesian Graph Neural Network for Fast identification of critical nodes in Uncertain Complex Networks
Sai Munikoti, Laya Das, Balasubramaniam Natarajan
In the quest to improve efficiency, interdependence and complexity are becoming defining characteristics of modern complex networks representing engineered and natural systems. Gra…
Scalable Graph Neural Network-based framework for identifying critical nodes and links in Complex Networks
Sai Munikoti, Laya Das, Balasubramaniam Natarajan
Identifying critical nodes and links in graphs is a crucial task. These nodes/links typically represent critical elements/communication links that play a key role in a system's per…
Probabilistic Voltage Sensitivity Analysis (PVSA) to Quantify Impact of High PV Penetration on Unbalanced Distribution System
Sai Munikoti, Balasubramaniam Natarajan, Kumarsinh Jhala +1
From an operational and planning perspective, it is important to quantify the impact of increasing penetration of photovoltaics on the distribution system. Most existing impact ass…
Analytical Voltage Sensitivity Analysis for Unbalanced Power Distribution System
Sai Munikoti, Kumarsinh Jhala, Kexing Lai +1
Large scale integration of distributed energy resources and electric vehicles in a transactive energy environment present new challenges in terms of voltage stability and fluctuati…
Spatio-Temporal Probabilistic Voltage Sensitivity Analysis - A Novel Framework for Hosting Capacity Analysis
Sai Munikoti, Mohammad Abujubbeh, Kumarsinh Jhala +1
Smart grids are envisioned to accommodate high penetration of distributed photovoltaic (PV) generation, which may cause adverse grid impacts in terms of voltage violations. Therefo…
Robustness Assessment of Hetero-Functional Graph Theory Based Model of Interdependent Urban Utility Networks
Sai Munikoti, Kexing Lai, Balasubramaniam Natarajan
The increasing urban population imposes a substantial and growing burden on the supporting infrastructure, such as electricity, water, heating, natural gas, road transportation, et…
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…