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ORCIDSai Munikoti
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2020 – today
- 2024
[i23]Sai Munikoti, Ian Stewart, Sameera Horawalavithana, Henry Kvinge, Tegan Emerson, Sandra E. Thompson, Karl Pazdernik:
Generalist Multimodal AI: A Review of Architectures, Challenges and Opportunities. CoRR abs/2406.05496 (2024)- [i22]Hung Phan, Anurag Acharya, Sarthak Chaturvedi, Shivam Sharma, Mike Parker, Dan Nally, Ali Jannesari, Karl Pazdernik, Mahantesh Halappanavar, Sai Munikoti, Sameera Horawalavithana:
RAG vs. Long Context: Examining Frontier Large Language Models for Environmental Review Document Comprehension. CoRR abs/2407.07321 (2024) - [i21]Rounak Meyur, Hung Phan, Sridevi Wagle, Jan Strube, Mahantesh Halappanavar, Sameera Horawalavithana, Anurag Acharya, Sai Munikoti:
PermitQA: A Benchmark for Retrieval Augmented Generation in Wind Siting and Permitting domain. CoRR abs/2408.11800 (2024) - [i20]Ian Stewart, Sameera Horawalavithana, Brendan Kennedy, Sai Munikoti, Karl Pazdernik:
Surprisingly Fragile: Assessing and Addressing Prompt Instability in Multimodal Foundation Models. CoRR abs/2408.14595 (2024) - 2023
- [j5]Sai Munikoti
, Deepesh Agarwal, Laya Das, Balasubramaniam Natarajan:
A general framework for quantifying aleatoric and epistemic uncertainty in graph neural networks. Neurocomputing 521: 1-10 (2023) - [c2]Shweta Dahale, Sai Munikoti, Balasubramaniam Natarajan, Rui Yang:
Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids. ISGT 2023: 1-5 - [i19]Laya Das, Sai Munikoti, Mahantesh Halappanavar:
There is more to graphs than meets the eye: Learning universal features with self-supervision. CoRR abs/2305.19871 (2023) - [i18]Shweta Dahale, Sai Munikoti, Balasubramaniam Natarajan:
A General Framework for Uncertainty Quantification via Neural SDE-RNN. CoRR abs/2306.01189 (2023) - [i17]Sameera Horawalavithana, Sai Munikoti, Ian Stewart, Henry Kvinge:
SCITUNE: Aligning Large Language Models with Scientific Multimodal Instructions. CoRR abs/2307.01139 (2023) - [i16]Anurag Acharya, Sai Munikoti, Aaron Hellinger, Sara Smith, Sridevi Wagle, Sameera Horawalavithana:
NuclearQA: A Human-Made Benchmark for Language Models for the Nuclear Domain. CoRR abs/2310.10920 (2023) - [i15]Sai Munikoti, Anurag Acharya, Sridevi Wagle, Sameera Horawalavithana:
Evaluating the Effectiveness of Retrieval-Augmented Large Language Models in Scientific Document Reasoning. CoRR abs/2311.04348 (2023) - [i14]Sridevi Wagle, Sai Munikoti, Anurag Acharya, Sara Smith, Sameera Horawalavithana:
Empirical evaluation of Uncertainty Quantification in Retrieval-Augmented Language Models for Science. CoRR abs/2311.09358 (2023) - [i13]Sai Munikoti, Anurag Acharya, Sridevi Wagle, Sameera Horawalavithana:
ATLANTIC: Structure-Aware Retrieval-Augmented Language Model for Interdisciplinary Science. CoRR abs/2311.12289 (2023) - 2022
- [j4]Sai Munikoti, Mohammad Abujubbeh, Balasubramaniam Natarajan:
Robustness of Power Distribution System: A Comparative Study of Network and Performance Based Metrics. IEEE Access 10: 82531-82539 (2022) - [j3]Sai Munikoti, Laya Das, Balasubramaniam Natarajan:
Scalable graph neural network-based framework for identifying critical nodes and links in complex networks. Neurocomputing 468: 211-221 (2022) - [i12]Sai Munikoti, Deepesh Agarwal, Laya Das, Balasubramaniam Natarajan:
A General Framework for quantifying Aleatoric and Epistemic uncertainty in Graph Neural Networks. CoRR abs/2205.09968 (2022) - [i11]Sai Munikoti, Balasubramaniam Natarajan, Mahantesh Halappanavar:
GraMeR: Graph Meta Reinforcement Learning for Multi-Objective Influence Maximization. CoRR abs/2205.14834 (2022) - [i10]Sai Munikoti, Deepesh Agarwal, Laya Das, Mahantesh Halappanavar, Balasubramaniam Natarajan:
Challenges and Opportunities in Deep Reinforcement Learning with Graph Neural Networks: A Comprehensive review of Algorithms and Applications. CoRR abs/2206.07922 (2022) - [i9]Shweta Dahale, Sai Munikoti, Balasubramaniam Natarajan, Rui Yang:
Latent Neural ODE for Integrating Multi-timescale measurements in Smart Distribution Grids. CoRR abs/2211.03882 (2022) - 2021
- [j2]Sai Munikoti, Kexing Lai, Balasubramaniam Natarajan:
Robustness assessment of Hetero-functional graph theory based model of interdependent urban utility networks. Reliab. Eng. Syst. Saf. 212: 107627 (2021) - [c1]Sai Munikoti, Laya Das, Balasubramaniam Natarajan:
Bayesian Graph Neural Network for Fast identification of critical nodes in Uncertain Complex Networks. SMC 2021: 3245-3251 - [i8]Sai Munikoti, Mohammad Abujubbeh, Kumarsinh Jhala, Balasubramaniam Natarajan:
An Information Theoretic approach to identify Dominant Voltage Influencers for Unbalanced Distribution Systems. CoRR abs/2106.01587 (2021) - 2020
- [i7]Mohammad Abujubbeh, Sai Munikoti, Balasubramaniam Natarajan:
Probabilistic Voltage Sensitivity based Preemptive Voltage Monitoring in Unbalanced Distribution Networks. CoRR abs/2008.10814 (2020) - [i6]Sai Munikoti, Kexing Lai, Balasubramaniam Natarajan:
Robustness Assessment of Hetero-Functional Graph Theory Based Model of Interdependent Urban Utility Networks. CoRR abs/2008.11831 (2020) - [i5]Sai Munikoti, Kumarsinh Jhala, Kexing Lai, Balasubramaniam Natarajan:
Analytical Voltage Sensitivity Analysis for Unbalanced Power Distribution System. CoRR abs/2009.05513 (2020) - [i4]Sai Munikoti, Balasubramaniam Natarajan, Kumarsinh Jhala, Kexing Lai:
Probabilistic Voltage Sensitivity Analysis (PVSA) to Quantify Impact of High PV Penetration on Unbalanced Distribution System. CoRR abs/2009.05734 (2020) - [i3]Sai Munikoti, Mohammad Abujubbeh, Kumarsinh Jhala, Balasubramaniam Natarajan:
Spatio-Temporal Probabilistic Voltage Sensitivity Analysis (ST-PVSA)-A Novel Framework for Hosting Capacity Analysis. CoRR abs/2009.08490 (2020) - [i2]Sai Munikoti, Laya Das, Balasubramaniam Natarajan:
Graph neural network based approximation of Node Resiliency in complex networks. CoRR abs/2012.15725 (2020) - [i1]Sai Munikoti, Balasubramaniam Natarajan:
Bayesian Inductive Learner for Graph Resiliency under uncertainty. CoRR abs/2012.15733 (2020)
2010 – 2019
- 2019
- [j1]Sai Munikoti, Laya Das, Balasubramaniam Natarajan, Babji Srinivasan:
Data-Driven Approaches for Diagnosis of Incipient Faults in DC Motors. IEEE Trans. Ind. Informatics 15(9): 5299-5308 (2019)
Coauthor Index
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