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ORCIDNikhil Muralidhar
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2020 – today
- 2024
[j4]Shengzhe Xu
, Christo Kurisummoottil Thomas, Omar Hashash, Nikhil Muralidhar, Walid Saad, Naren Ramakrishnan:
Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems. IEEE Netw. 38(5): 10-20 (2024)- [c16]Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar:
Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation. AAAI 2024: 15066-15074 - [c15]Mandar Sharma, Rutuja Murlidhar Taware, Pravesh Koirala, Nikhil Muralidhar, Naren Ramakrishnan:
Laying Anchors: Semantically Priming Numerals in Language Modeling. NAACL-HLT (Findings) 2024: 2653-2660 - [i12]Shengzhe Xu, Christo Kurisummoottil Thomas, Omar Hashash, Nikhil Muralidhar, Walid Saad, Naren Ramakrishnan:
Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems. CoRR abs/2402.01748 (2024) - [i11]Bharat Srikishan, Anika Tabassum, Srikanth Allu, Ramakrishnan Kannan, Nikhil Muralidhar:
Reinforcement Learning as a Parsimonious Alternative to Prediction Cascades: A Case Study on Image Segmentation. CoRR abs/2402.11760 (2024) - [i10]Mandar Sharma, Rutuja Murlidhar Taware, Pravesh Koirala, Nikhil Muralidhar, Naren Ramakrishnan:
Laying Anchors: Semantically Priming Numerals in Language Modeling. CoRR abs/2404.01536 (2024) - [i9]Mandar Sharma, Nikhil Muralidhar, Shengzhe Xu, Raquib Bin Yousuf, Naren Ramakrishnan:
Information Guided Regularization for Fine-tuning Language Models. CoRR abs/2406.14005 (2024) - [i8]Shengzhe Xu, Cho-Ting Lee, Mandar Sharma, Raquib Bin Yousuf, Nikhil Muralidhar, Naren Ramakrishnan:
Are LLMs Naturally Good at Synthetic Tabular Data Generation? CoRR abs/2406.14541 (2024) - 2023
- [c14]Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan:
Learning Non-linguistic Skills without Sacrificing Linguistic Proficiency. ACL (1) 2023: 6178-6191 - [c13]Abhinav Prasad, Prakash Arunachalam, Ali Motamedi, Ranjeeta Bhattacharya, Beibei Liu, Hays McCormick, Shengzhe Xu, Nikhil Muralidhar, Naren Ramakrishnan:
ML-Assisted Optimization of Securities Lending. ICAIF 2023: 628-636 - [i7]Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan:
Learning Non-linguistic Skills without Sacrificing Linguistic Proficiency. CoRR abs/2305.08246 (2023) - 2022
- [b1]Nikhil Muralidhar:
Science Guided Machine Learning: Incorporating Scientific Domain Knowledge for Learning Under Data Paucity and Noisy Contexts. Virginia Tech, Blacksburg, VA, USA, 2022 - [c12]Anika Tabassum, Nikhil Muralidhar, Ramakrishnan Kannan, Srikanth Allu:
MatPhase: Material phase prediction for Li-ion Battery Reconstruction using Hierarchical Curriculum Learning. IEEE Big Data 2022: 1936-1941 - [c11]Gopikrishna Rathinavel, Nikhil Muralidhar, Timothy J. O'Shea, Naren Ramakrishnan:
Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback. ICDM 2022: 1161-1166 - [c10]Gopikrishna Rathinavel, Nikhil Muralidhar, Naren Ramakrishnan, Timothy J. O'Shea:
Efficient Generative Wireless Anomaly Detection for Next Generation Networks. MILCOM 2022: 594-599 - [i6]Nikhil Muralidhar, Abdullah Zubair, Nathanael R. Weidler, Ryan M. Gerdes, Naren Ramakrishnan:
Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores. CoRR abs/2203.02095 (2022) - [i5]Gopikrishna Rathinavel, Nikhil Muralidhar, Timothy J. O'Shea, Naren Ramakrishnan:
Detecting Irregular Network Activity with Adversarial Learning and Expert Feedback. CoRR abs/2210.02841 (2022) - [i4]Mandar Sharma, Nikhil Muralidhar, Naren Ramakrishnan:
Overcoming Barriers to Skill Injection in Language Modeling: Case Study in Arithmetic. CoRR abs/2211.02098 (2022) - 2021
- [c9]Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash:
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. AAAI 2021: 4855-4863 - [c8]Nikhil Muralidhar, Abdullah Zubair, Nathanael R. Weidler, Ryan M. Gerdes, Naren Ramakrishnan:
Contrastive Graph Convolutional Networks for Hardware Trojan Detection in Third Party IP Cores. HOST 2021: 181-191 - [c7]Nikhil Muralidhar, Jie Bu, Ze Cao, Neil Raj, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
PhyFlow: Physics-Guided Deep Learning for Generating Interpretable 3D Flow Fields. ICDM 2021: 1246-1251 - [i3]Nikhil Muralidhar, Sathappan Muthiah, Patrick Butler, Manish Jain, Yu Yu, Katy Burne, Weipeng Li, David Jones, Prakash Arunachalam, Hays 'Skip' McCormick, Naren Ramakrishnan:
Using AntiPatterns to avoid MLOps Mistakes. CoRR abs/2107.00079 (2021) - 2020
- [j3]Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems. Big Data 8(5): 431-449 (2020) - [j2]Nikhil Muralidhar, Anika Tabassum, Liangzhe Chen, Supriya Chinthavali, Naren Ramakrishnan, B. Aditya Prakash:
Cut-n-Reveal: Time Series Segmentations with Explanations. ACM Trans. Intell. Syst. Technol. 11(5): 53:1-53:26 (2020) - [c6]Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
PhyNet: Physics Guided Neural Networks for Particle Drag Force Prediction in Assembly. SDM 2020: 559-567 - [i2]Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash:
Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19. CoRR abs/2009.11407 (2020)
2010 – 2019
- 2019
- [c5]Nikhil Muralidhar, Sathappan Muthiah, Kiyoshi Nakayama, Ratnesh Sharma, Naren Ramakrishnan:
Multivariate Long-Term State Forecasting in Cyber-Physical Systems: A Sequence to Sequence Approach. IEEE BigData 2019: 543-552 - [c4]Kiyoshi Nakayama, Nikhil Muralidhar, Chenrui Jin, Ratnesh Sharma:
Detection of False Data Injection Attacks in Cyber-Physical Systems using Dynamic Invariants. ICMLA 2019: 1023-1030 - [c3]Nikhil Muralidhar, Sathappan Muthiah, Naren Ramakrishnan:
DyAt Nets: Dynamic Attention Networks for State Forecasting in Cyber-Physical Systems. IJCAI 2019: 3180-3186 - [i1]Nikhil Muralidhar, Jie Bu, Ze Cao, Long He, Naren Ramakrishnan, Danesh K. Tafti, Anuj Karpatne:
Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids. CoRR abs/1911.04240 (2019) - 2018
- [j1]Nikhil Muralidhar, Chen Wang, Nathan Self, Marjan Momtazpour, Kiyoshi Nakayama, Ratnesh Sharma, Naren Ramakrishnan:
illiad: InteLLigent Invariant and Anomaly Detection in Cyber-Physical Systems. ACM Trans. Intell. Syst. Technol. 9(3): 35:1-35:20 (2018) - [c2]Nikhil Muralidhar, Mohammad Raihanul Islam, Manish Marwah, Anuj Karpatne, Naren Ramakrishnan:
Incorporating Prior Domain Knowledge into Deep Neural Networks. IEEE BigData 2018: 36-45 - 2015
- [c1]Nikhil Muralidhar, Huzefa Rangwala, Eui-Hong Sam Han:
Recommending Temporally Relevant News Content from Implicit Feedback Data. ICTAI 2015: 689-696
Coauthor Index
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