Harshavardhan Kamarthi

38 papers A* 10A 3Journal 23Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	AHA: Scalable Alternative History Analysis for Operational Timeseries Applications. KDD (1) Harshavardhan Kamarthi, Harshil Shah, Henry Milner, Sayan Sinha, Yan Li, B. Aditya Prakash, Vyas Sekar
2026	J	`jnl`	AHA: Scalable Alternative History Analysis for Operational Timeseries Applications. CoRR Harshavardhan Kamarthi, Harshil Shah, Henry Milner, Sayan Sinha, Yan Li, B. Aditya Prakash, Vyas Sekar
2026	J	`jnl`	Hierarchical Industrial Demand Forecasting with Temporal and Uncertainty Explanations. CoRR Harshavardhan Kamarthi, Shangqing Xu, Xinjie Tong, Xingyu Zhou, James Peters, Joseph Czyzyk, B. Aditya Prakash
2026	J	`jnl`	In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks. CoRR Shangqing Xu, Harshavardhan Kamarthi, Haoxin Liu, B. Aditya Prakash
2026	J	`jnl`	Seeking Universal Shot Language Understanding Solutions. CoRR Haoxin Liu, Harshavardhan Kamarthi, Zhiyuan Zhao, Hongjie Chen, B. Aditya Prakash
2025	J	`jnl`	How Can Time Series Analysis Benefit From Multiple Modalities? A Survey and Outlook. CoRR Haoxin Liu, Harshavardhan Kamarthi, Zhiyuan Zhao, Shangqing Xu, Shiyu Wang, Qingsong Wen, Tom Hartvigsen, Fei Wang, B. Aditya Prakash
2025	A	`conf`	In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks. CIKM Shangqing Xu, Harshavardhan Kamarthi, Haoxin Liu, B. Aditya Prakash
2024	—	`conf`	LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. ACL (Findings) Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash
2024	J	`jnl`	LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. CoRR Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash
2024	A*	`conf`	Large Pre-trained time series models for cross-domain Time series analysis tasks. NeurIPS Harshavardhan Kamarthi, B. Aditya Prakash
2024	A*	`conf`	Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity. KDD Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, B. Aditya Prakash
2024	J	`jnl`	Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity. CoRR Harshavardhan Kamarthi, Aditya B. Sasanur, Xinjie Tong, Xingyu Zhou, James Peters, Joe Czyzyk, B. Aditya Prakash
2024	J	`jnl`	Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting. CoRR Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
2024	J	`jnl`	Machine learning for data-centric epidemic forecasting. Nat. Mac. Intell. Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, Javen Ho, Mira Patel, Suchet Sapre, B. Aditya Prakash
2024	J	`jnl`	Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis. CoRR Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash
2024	A*	`conf`	Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis. NeurIPS Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash
2024	A*	`conf`	Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. ICML Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash
2024	J	`jnl`	Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. CoRR Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash
2023	J	`jnl`	Large Pre-trained time series models for cross-domain Time series analysis tasks. CoRR Harshavardhan Kamarthi, B. Aditya Prakash
2023	J	`jnl`	PEMS: Pre-trained Epidemic Time-series Models. CoRR Harshavardhan Kamarthi, B. Aditya Prakash
2023	A*	`conf`	Uncertainty Quantification in Deep Learning. KDD Lingkai Kong, Harshavardhan Kamarthi, Peng Chen, B. Aditya Prakash, Chao Zhang
2023	A*	`conf`	When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. KDD Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
2022	A*	`conf`	Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. ICLR Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash
2022	A*	`conf`	CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. WWW Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
2022	J	`jnl`	Data-Centric Epidemic Forecasting: A Survey. CoRR Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, Javen Ho, Mira Patel, Suchet Sapre, B. Aditya Prakash
2022	A*	`conf`	Epidemic Forecasting with a Data-Centric Lens. KDD Alexander Rodríguez, Harshavardhan Kamarthi, B. Aditya Prakash
2022	J	`jnl`	PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series. CoRR Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
2021	J	`jnl`	Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. CoRR Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash
2021	J	`jnl`	CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. CoRR Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
2021	A	`conf`	Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. AAMAS Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe
2021	J	`jnl`	Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes. CoRR Siddharth Nishtala, Lovish Madaan, Aditya Mate, Harshavardhan Kamarthi, Anirudh Grama, Divy Thakkar, Dhyanesh Narayanan, Suresh Chaudhary, Neha Madhiwalla, Ramesh Padmanabhan, Aparna Hegde, Pradeep Varakantham, Balaraman Ravindran, Milind Tambe
2021	A*	`conf`	When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. NeurIPS Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
2021	J	`jnl`	When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. CoRR Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash
2020	A	`conf`	Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. AAMAS Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe
2020	J	`jnl`	Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement. CoRR Siddharth Nishtala, Harshavardhan Kamarthi, Divy Thakkar, Dhyanesh Narayanan, Anirudh Grama, Ramesh Padmanabhan, Neha Madhiwalla, Suresh Chaudhary, Balaraman Ravindran, Milind Tambe
2020	J	`jnl`	Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. CoRR Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe
2019	J	`jnl`	Integrating Lexical Knowledge in Word Embeddings using Sprinkling and Retrofitting. CoRR Aakash Srinivasan, Harshavardhan Kamarthi, Devi Ganesan, Sutanu Chakraborti
2019	J	`jnl`	Learning policies for Social network discovery with Reinforcement learning. CoRR Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe