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ORCIDVignesh Narayanan
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2020 – today
- 2024
[j19]Chathurangi Shyalika
, Kaushik Roy, Renjith Prasad, Fadi El Kalach, Yuxin Zi, Priya Mittal, Vignesh Narayanan, Ramy F. Harik, Amit P. Sheth:
RI2AP: Robust and Interpretable 2D Anomaly Prediction in Assembly Pipelines. Sensors 24(10): 3244 (2024)- [j18]Vignesh Narayanan, Wei Zhang, Jr-Shin Li:
Duality of Ensemble Systems Through Moment Representations. IEEE Trans. Autom. Control. 69(10): 7270-7276 (2024) - [j17]Krishnan Raghavan, Vignesh Narayanan, Sarangapani Jagannathan:
Cooperative Deep Q-Learning Framework for Environments Providing Image Feedback. IEEE Trans. Neural Networks Learn. Syst. 35(7): 9267-9276 (2024) - [j16]Yao-Chi Yu, Vignesh Narayanan, Jr-Shin Li:
Moment-Based Reinforcement Learning for Ensemble Control. IEEE Trans. Neural Networks Learn. Syst. 35(9): 12653-12664 (2024) - [c29]Bharath Muppasani, Vignesh Narayanan, Biplav Srivastava, Michael N. Huhns:
Expressive and Flexible Simulation of Information Spread Strategies in Social Networks Using Planning. AAAI 2024: 23820-23822 - [c28]Kaushik Roy, Alessandro Oltramari, Yuxin Zi, Chathurangi Shyalika, Vignesh Narayanan, Amit P. Sheth:
Causal Event Graph-Guided Language-based Spatiotemporal Question Answering. AAAI Spring Symposia 2024: 227-233 - [c27]Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Amit P. Sheth:
Exploring Alternative Approaches to Language Modeling for Learning from Data and Knowledge. AAAI Spring Symposia 2024: 279-286 - [c26]Maxwell Geiger, Vignesh Narayanan, Sarangapani Jagannathan:
Optimal Tracking of Uncertain Linear Discrete-Time Systems Using Trajectory-Dependent Lifelong Q-learning. ACC 2024: 3631-3636 - [i15]Bharath Muppasani, Protik Nag, Vignesh Narayanan, Biplav Srivastava, Michael N. Huhns:
Towards Effective Planning Strategies for Dynamic Opinion Networks. CoRR abs/2410.14091 (2024) - 2023
- [j15]Bharath Muppasani, Vishal Pallagani, Kausik Lakkaraju, Shuge Lei, Biplav Srivastava, Brett W. Robertson, Andrea Hickerson, Vignesh Narayanan:
On safe and usable chatbots for promoting voter participation. AI Mag. 44(3): 240-247 (2023) - [j14]Wei Miao, Vignesh Narayanan, Jr-Shin Li:
Interpretable Design of Reservoir Computing Networks Using Realization Theory. IEEE Trans. Neural Networks Learn. Syst. 34(9): 6379-6389 (2023) - [j13]Rohollah Moghadam, Vignesh Narayanan, Sarangapani Jagannathan:
Event-Triggered Optimal Adaptive Control of Partially Unknown Linear Continuous-Time Systems With State Delay. IEEE Trans. Syst. Man Cybern. Syst. 53(6): 3324-3337 (2023) - [c25]Geetika Vennam, Avimanyu Sahoo, Vignesh Narayanan:
Core Temperature Estimation of Lithium-ion Batteries Under Internal Thermal Faults Using Neural Networks. CCTA 2023: 376-381 - [c24]Revathy Venkataramanan, Kaushik Roy, Kanak Raj, Renjith Prasad, Yuxin Zi, Vignesh Narayanan, Amit P. Sheth:
Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes. SMC 2023: 981-986 - [i14]Kaushik Roy, Tarun Garg, Vedant Palit, Yuxin Zi, Vignesh Narayanan, Amit P. Sheth:
Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust. CoRR abs/2305.04989 (2023) - [i13]Revathy Venkataramanan, Kaushik Roy, Kanak Raj, Renjith Prasad, Yuxin Zi, Vignesh Narayanan, Amit P. Sheth:
Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes. CoRR abs/2306.01805 (2023) - [i12]Kaushik Roy, Yuxin Zi, Manas Gaur, Jinendra Malekar, Qi Zhang, Vignesh Narayanan, Amit P. Sheth:
Process Knowledge-infused Learning for Clinician-friendly Explanations. CoRR abs/2306.09824 (2023) - [i11]Kaushik Roy, Yuxin Zi, Vignesh Narayanan, Manas Gaur, Amit P. Sheth:
Knowledge-Infused Self Attention Transformers. CoRR abs/2306.13501 (2023) - [i10]Yuxin Zi, Kaushik Roy, Vignesh Narayanan, Manas Gaur, Amit P. Sheth:
IERL: Interpretable Ensemble Representation Learning - Combining CrowdSourced Knowledge and Distributed Semantic Representations. CoRR abs/2306.13865 (2023) - [i9]Bharath Muppasani, Vishal Pallagani, Biplav Srivastava, Raghava Mutharaju, Michael N. Huhns, Vignesh Narayanan:
A Planning Ontology to Represent and Exploit Planning Knowledge for Performance Efficiency. CoRR abs/2307.13549 (2023) - [i8]Biplav Srivastava, Kausik Lakkaraju, Tarmo Koppel, Vignesh Narayanan, Ashish Kundu, Sachindra Joshi:
Evaluating Chatbots to Promote Users' Trust - Practices and Open Problems. CoRR abs/2309.05680 (2023) - 2022
- [j12]Vignesh Narayanan, Hamidreza Modares, Sarangapani Jagannathan, Frank L. Lewis:
Event-Driven Off-Policy Reinforcement Learning for Control of Interconnected Systems. IEEE Trans. Cybern. 52(3): 1936-1946 (2022) - [i7]Shrey Gupta, Anmol Agarwal, Manas Gaur, Kaushik Roy, Vignesh Narayanan, Ponnurangam Kumaraguru, Amit P. Sheth:
Learning to Automate Follow-up Question Generation using Process Knowledge for Depression Triage on Reddit Posts. CoRR abs/2205.13884 (2022) - [i6]Kaushik Roy, Yuxin Zi, Vignesh Narayanan, Manas Gaur, Amit P. Sheth:
KSAT: Knowledge-infused Self Attention Transformer - Integrating Multiple Domain-Specific Contexts. CoRR abs/2210.04307 (2022) - [i5]Bharath Muppasani, Vishal Pallagani, Kausik Lakkaraju, Shuge Lei, Biplav Srivastava, Brett W. Robertson, Andrea Hickerson, Vignesh Narayanan:
On Safe and Usable Chatbots for Promoting Voter Participation. CoRR abs/2212.11219 (2022) - 2021
- [j11]Liang Wang, Vignesh Narayanan, Yao-Chi Yu, Yikyung Park, Jr-Shin Li:
A Nested Two-Stage Clustering Method for Structured Temporal Sequence Data. Knowl. Inf. Syst. 63(7): 1627-1662 (2021) - [j10]Wei-Cheng Jiang, Vignesh Narayanan, Jr-Shin Li:
Model Learning and Knowledge Sharing for Cooperative Multiagent Systems in Stochastic Environment. IEEE Trans. Cybern. 51(12): 5717-5727 (2021) - [c23]Avimanyu Sahoo, Vignesh Narayanan, Qiming Zhao:
Adaptive Gain Observers for Distributed State Estimation of Linear Systems. ACC 2021: 298-303 - [c22]Vignesh Narayanan, Brett W. Robertson, Andrea Hickerson, Biplav Srivastava, Bryant Walker Smith:
Securing social media for seniors from information attacks: Modeling, detecting, intervening, and communicating risks. TPS-ISA 2021: 297-302 - [i4]Krishnan Raghavan, Vignesh Narayanan, Jagannathan Saraangapani:
Learning to Control using Image Feedback. CoRR abs/2110.15290 (2021) - [i3]Raghavan Krishnan, Vignesh Narayanan, Jagannathan Sarangapani:
Cooperative Deep Q-learning Framework for Environments Providing Image Feedback. CoRR abs/2110.15305 (2021) - [i2]Wei Miao, Vignesh Narayanan, Jr-Shin Li:
Interpretable Design of Reservoir Computing Networks using Realization Theory. CoRR abs/2112.06891 (2021) - 2020
- [j9]Avimanyu Sahoo, Vignesh Narayanan:
Differential-game for resource aware approximate optimal control of large-scale nonlinear systems with multiple players. Neural Networks 124: 95-108 (2020) - [c21]Yao-Chi Yu, Vignesh Narayanan, ShiNung Ching, Jr-Shin Li:
Learning to Control Neurons using Aggregated Measurements. ACC 2020: 4028-4033 - [c20]Avimanyu Sahoo, Vignesh Narayanan, Qiming Zhao:
Finite-time Adaptive Optimal Output Feedback Control of Linear Systems with Intermittent Feedback. SSCI 2020: 233-240
2010 – 2019
- 2019
- [j8]Vignesh Narayanan, Jr-Shin Li, ShiNung Ching:
Biophysically interpretable inference of single neuron dynamics. J. Comput. Neurosci. 47(1): 61-76 (2019) - [j7]Avimanyu Sahoo, Vignesh Narayanan:
Optimization of sampling intervals for tracking control of nonlinear systems: A game theoretic approach. Neural Networks 114: 78-90 (2019) - [j6]Avimanyu Sahoo, Vignesh Narayanan, Sarangapani Jagannathan:
A Min-Max Approach to Event- and Self-Triggered Sampling and Regulation of Linear Systems. IEEE Trans. Ind. Electron. 66(7): 5433-5440 (2019) - [j5]Vignesh Narayanan, Avimanyu Sahoo, Sarangapani Jagannathan, Koshy George:
Approximate Optimal Distributed Control of Nonlinear Interconnected Systems Using Event-Triggered Nonzero-Sum Games. IEEE Trans. Neural Networks Learn. Syst. 30(5): 1512-1522 (2019) - [j4]Vignesh Narayanan, Sarangapani Jagannathan, Kannan Ramkumar:
Event-Sampled Output Feedback Control of Robot Manipulators Using Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 30(6): 1651-1658 (2019) - [c19]Vignesh Narayanan, Jason T. Ritt, Jr-Shin Li, ShiNung Ching:
A Learning Framework for Controlling Spiking Neural Networks. ACC 2019: 211-216 - [c18]Wei Zhang, Vignesh Narayanan, Jr-Shin Li:
Robust Population Transfer for Coupled Spin Ensembles. CDC 2019: 419-424 - 2018
- [j3]Vignesh Narayanan, Sarangapani Jagannathan:
Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration. IEEE Trans. Cybern. 48(9): 2510-2519 (2018) - [j2]Nathan Szanto, Vignesh Narayanan, Sarangapani Jagannathan:
Event-Sampled Direct Adaptive NN Output- and State-Feedback Control of Uncertain Strict-Feedback System. IEEE Trans. Neural Networks Learn. Syst. 29(5): 1850-1863 (2018) - [j1]Vignesh Narayanan, Sarangapani Jagannathan:
Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems. IEEE Trans. Neural Networks Learn. Syst. 29(7): 2846-2856 (2018) - [c17]Vignesh Narayanan, Avimanyu Sahoo, Sarangapani Jagannathan:
Optimal Event-triggered Control of Nonlinear Systems: A Min-max Approach. ACC 2018: 3441-3446 - [c16]Avimanyu Sahoo, Vignesh Narayanan:
Event-based Near Optimal Sampling and Tracking Control of Nonlinear Systems. CDC 2018: 55-60 - [c15]Vignesh Narayanan, Avimanyu Sahoo, Sarangapani Jagannathan:
Approximate Optimal Distributed Control of Nonlinear Interconnected Systems Using Nonzero-Sum Games. CDC 2018: 2872-2877 - [c14]Vignesh Narayanan, Avimanyu Sahoo, Sarangapani Jagannathan:
Adaptive Optimal Distributed Control of Linear Interconnected Systems. SSCI 2018: 1441-1446 - [c13]Avimanyu Sahoo, Vignesh Narayanan, Sarangapani Jagannathan:
Event-triggered Control of N-player Nonlinear Systems Using Nonzero-Sum Games. SSCI 2018: 1447-1452 - 2017
- [c12]Nathan Szanto, Vignesh Narayanan, Sarangapani Jagannathan:
Event-sampled control of quadrotor unmanned aerial vehicle using neural networks. ACC 2017: 2956-2961 - [c11]Haci Mehmet Guzey, Vignesh Narayanan, Sarangapani Jagannathan, Travis Dierks, Levent Acar:
Distributed consensus-based event-triggered approximate control of nonholonomic mobile robot formations. ACC 2017: 3194-3199 - [c10]Vignesh Narayanan, Sarangapani Jagannathan:
Online reinforcement with exploration for distributed control. IJCNN 2017: 4022-4027 - [c9]Avimanyu Sahoo, Vignesh Narayanan, Sarangapani Jagannathan:
Optimal sampling and regulation of uncertain interconnected linear continuous time systems. SSCI 2017: 1-6 - [c8]Avimanyu Sahoo, Vignesh Narayanan, Sarangapani Jagannathan:
Optimal event-triggered control of uncertain linear networked control systems: A co-design approach. SSCI 2017: 1-6 - 2016
- [c7]Vignesh Narayanan, Sarangapani Jagannathan:
Distributed event-sampled approximate optimal control of interconnected affine nonlinear continuous-time systems. ACC 2016: 3044-3049 - [c6]Nathan Szanto, Vignesh Narayanan, Sarangapani Jagannathan:
Event-sampled direct adaptive NN state-feedback control of uncertain strict-feedback system. CDC 2016: 3395-3400 - [c5]Vignesh Narayanan, Sarangapani Jagannathan:
Approximate optimal distributed control of uncertain nonlinear interconnected systems with event-sampled feedback. CDC 2016: 5827-5832 - [c4]Vignesh Narayanan, Sarangapani Jagannathan:
Event-sampled adaptive neural network control of robot manipulators. IJCNN 2016: 4941-4946 - 2015
- [c3]Vignesh Narayanan, Yu Zhang, Nathaniel Mendoza, Subbarao Kambhampati:
Automated Planning for Peer-to-peer Teaming and its Evaluation in Remote Human-Robot Interaction. HRI (Extended Abstracts) 2015: 161-162 - [c2]Yu Zhang, Vignesh Narayanan, Tathagata Chakraborti, Subbarao Kambhampati:
A human factors analysis of proactive support in human-robot teaming. IROS 2015: 3586-3593 - [c1]Vignesh Narayanan, Sarangapani Jagannathan:
Distributed Adaptive Optimal Regulation of Uncertain Large-Scale Linear Networked Control Systems Using Q-Learning. SSCI 2015: 587-592 - 2014
- [i1]Vignesh Narayanan, Yu Zhang, Nathaniel Mendoza, Subbarao Kambhampati:
Plan or not: Remote Human-robot Teaming with Incomplete Task Information. CoRR abs/1412.2824 (2014)
Coauthor Index
aka: Jagannathan Sarangapani
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