| Influence maximization in unknown social networks: Learning policies for effective graph sampling H Kamarthi, P Vijayan, B Wilder, B Ravindran, M Tambe arXiv preprint arXiv:1907.11625, 2019 | 47 | 2019 |
| Data-centric epidemic forecasting: A survey A Rodríguez, H Kamarthi, P Agarwal, J Ho, M Patel, S Sapre, BA Prakash arXiv preprint arXiv:2207.09370, 2022 | 16 | 2022 |
| Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement S Nishtala, H Kamarthi, D Thakkar, D Narayanan, A Grama, A Hegde, ... arXiv preprint arXiv:2006.07590, 2020 | 16 | 2020 |
| Lingkai Kong, Alexander Rodríguez, Chao Zhang, and B Aditya Prakash. When in doubt: Neural non-parametric uncertainty quantification for epidemic forecasting H Kamarthi Advances in Neural Information Processing Systems 34, 19796-19807, 2021 | 15 | 2021 |
| CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting H Kamarthi, L Kong, A Rodríguez, C Zhang, BA Prakash Proceedings of the ACM Web Conference 2022, 3174-3185, 2022 | 11 | 2022 |
| Reinforcement learning for unified allocation and patrolling in signaling games with uncertainty A Venugopal, E Bondi, H Kamarthi, K Dholakia, B Ravindran, M Tambe arXiv preprint arXiv:2012.10389, 2020 | 11 | 2020 |
| Back2future: Leveraging backfill dynamics for improving real-time predictions in future H Kamarthi, A Rodríguez, BA Prakash arXiv preprint arXiv:2106.04420, 2021 | 10 | 2021 |
| When in doubt: Neural non-parametric uncertainty quantification for epidemic forecasting H Kamarthi, L Kong, A Rodriguez, C Zhang, BA Prakash Advances in Neural Information Processing Systems 34, 19796-19807, 2021 | 8 | 2021 |
| PROFHIT: Probabilistic robust forecasting for hierarchical time-series H Kamarthi, L Kong, A Rodríguez, C Zhang, BA Prakash arXiv preprint arXiv:2206.07940, 2022 | 7 | 2022 |
| Selective intervention planning using restless multi-armed bandits to improve maternal and child health outcomes S Nishtala, L Madaan, A Mate, H Kamarthi, A Grama, D Thakkar, ... arXiv preprint arXiv:2103.09052, 2021 | 5 | 2021 |
| Evaluation of FluSight influenza forecasting in the 2021–22 and 2022–23 seasons with a new target laboratory-confirmed influenza hospitalizations SM Mathis, AE Webber, TM León, EL Murray, M Sun, LA White, LC Brooks, ... medRxiv, 2023 | 3 | 2023 |
| Lingkai Kong, Alexander Rodriguez, Chao Zhang, and B Aditya Prakash. 2022 H Kamarthi CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. ACM The …, 2022 | 3 | 2022 |
| Large Pre-trained time series models for cross-domain Time series analysis tasks H Kamarthi, BA Prakash arXiv preprint arXiv:2311.11413, 2023 | 2 | 2023 |
| Integrating lexical knowledge in word embeddings using sprinkling and retrofitting A Srinivasan, H Kamarthi, D Ganesan, S Chakraborti arXiv preprint arXiv:1912.06889, 2019 | 2 | 2019 |
| PEMS: Pre-trained Epidmic Time-series Models H Kamarthi, BA Prakash arXiv preprint arXiv:2311.07841, 2023 | 1 | 2023 |
| Uncertainty Quantification in Deep Learning L Kong, H Kamarthi, P Chen, BA Prakash, C Zhang Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | 1 | 2023 |
| Epidemic Forecasting with a Data-Centric Lens A Rodríguez, H Kamarthi, BA Prakash Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 1 | 2022 |
| System and method for efficient language model editing using contextual prompt generator YC Hsu, H Kamarthi, Y Shen, H Jin US Patent App. 18/465,648, 2024 | | 2024 |
| LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting H Liu, Z Zhao, J Wang, H Kamarthi, BA Prakash arXiv preprint arXiv:2402.16132, 2024 | | 2024 |
| When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting H Kamarthi, L Kong, A Rodríguez, C Zhang, BA Prakash Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023 | | 2023 |
B. Aditya PrakashAssociate Professor, Georgia Institute of TechnologyVerified email at cs.cmu.edu
