Learning policies for Social network discovery with Reinforcement learning. - Harshavardhan Kamarthi; Priyesh Vijayan; Bryan Wilder; Balaraman Ravindran; Milind Tambe (CoRR, 2019)

Integrating Lexical Knowledge in Word Embeddings using Sprinkling and Retrofitting. - Aakash Srinivasan; Harshavardhan Kamarthi; Devi Ganesan; Sutanu Chakraborti (CoRR, 2019)

Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling. - Harshavardhan Kamarthi; Priyesh Vijayan; Bryan Wilder; Balaraman Ravindran; Milind Tambe (AAMAS, 2020)

Missed calls, Automated Calls and Health Support: Using AI to improve maternal health outcomes by increasing program engagement. - Siddharth Nishtala; Harshavardhan Kamarthi; Divy Thakkar; Dhyanesh Narayanan; Anirudh Grama; Ramesh Padmanabhan; Neha Madhiwalla; Suresh Chaudhary; Balaraman Ravindran; Milind Tambe (CoRR, 2020)

Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty. - Aravind Venugopal; Elizabeth Bondi; Harshavardhan Kamarthi; Keval Dholakia; Balaraman Ravindran; Milind Tambe (AAMAS, 2021)

When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting. - Harshavardhan Kamarthi; Lingkai Kong; Alexander Rodríguez; Chao Zhang 014; B. Aditya Prakash (NeurIPS, 2021)

Selective Intervention Planning using Restless Multi-Armed Bandits to Improve Maternal and Child Health Outcomes. - Siddharth Nishtala; Lovish Madaan; Aditya Mate; Harshavardhan Kamarthi; Anirudh Grama; Divy Thakkar; Dhyanesh Narayanan; Suresh Chaudhary; Neha Madhiwalla; Ramesh Padmanabhan; Aparna Hegde; Pradeep Varakantham; et al. (CoRR, 2021)

Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future. - Harshavardhan Kamarthi; Alexander Rodríguez; B. Aditya Prakash (ICLR, 2022)

Epidemic Forecasting with a Data-Centric Lens. - Alexander Rodríguez; Harshavardhan Kamarthi; B. Aditya Prakash (KDD, 2022)

CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting. - Harshavardhan Kamarthi; Lingkai Kong; Alexander Rodríguez; Chao Zhang 014; B. Aditya Prakash (WWW, 2022)

PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series. - Harshavardhan Kamarthi; Lingkai Kong; Alexander Rodríguez; Chao Zhang 014; B. Aditya Prakash (CoRR, 2022)

Data-Centric Epidemic Forecasting: A Survey. - Alexander Rodríguez; Harshavardhan Kamarthi; Pulak Agarwal; Javen Ho; Mira Patel; Suchet Sapre; B. Aditya Prakash (CoRR, 2022)

When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting. - Harshavardhan Kamarthi; Lingkai Kong; Alexander Rodríguez; Chao Zhang 014; B. Aditya Prakash (KDD, 2023)

Uncertainty Quantification in Deep Learning. - Lingkai Kong; Harshavardhan Kamarthi; Peng Chen 024; B. Aditya Prakash; Chao Zhang 014 (KDD, 2023)

PEMS: Pre-trained Epidemic Time-series Models. - Harshavardhan Kamarthi; B. Aditya Prakash (CoRR, 2023)

LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting. - Haoxin Liu 001; Zhiyuan Zhao 002; Jindong Wang 001; Harshavardhan Kamarthi; B. Aditya Prakash (ACL (Findings), 2024)

Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning. - Haoxin Liu 001; Harshavardhan Kamarthi; Lingkai Kong; Zhiyuan Zhao 002; Chao Zhang 014; B. Aditya Prakash (ICML, 2024)

Large Scale Hierarchical Industrial Demand Time-Series Forecasting incorporating Sparsity. - Harshavardhan Kamarthi; Aditya B. Sasanur; Xinjie Tong; Xingyu Zhou; James Peters; Joe Czyzyk; B. Aditya Prakash (KDD, 2024)

Large Pre-trained time series models for cross-domain Time series analysis tasks. - Harshavardhan Kamarthi; B. Aditya Prakash (NeurIPS, 2024)

Time-MMD: Multi-Domain Multimodal Dataset for Time Series Analysis. - Haoxin Liu 001; Shangqing Xu; Zhiyuan Zhao 002; Lingkai Kong; Harshavardhan Kamarthi; Aditya B. Sasanur; Megha Sharma; Jiaming Cui; Qingsong Wen; Chao Zhang 014; B. Aditya Prakash (NeurIPS, 2024)

Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis. - Haoxin Liu 001; Shangqing Xu; Zhiyuan Zhao 002; Lingkai Kong; Harshavardhan Kamarthi; Aditya B. Sasanur; Megha Sharma; Jiaming Cui; Qingsong Wen; Chao Zhang 014; B. Aditya Prakash (CoRR, 2024)

Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting. - Harshavardhan Kamarthi; Lingkai Kong; Alexander Rodríguez; Chao Zhang 014; B. Aditya Prakash (CoRR, 2024)

Machine learning for data-centric epidemic forecasting. - Alexander Rodríguez; Harshavardhan Kamarthi; Pulak Agarwal; Javen Ho; Mira Patel; Suchet Sapre; B. Aditya Prakash (Nat. Mac. Intell., 2024)

How Can Time Series Analysis Benefit From Multiple Modalities? A Survey and Outlook. - Haoxin Liu 001; Harshavardhan Kamarthi; Zhiyuan Zhao 002; Shangqing Xu; Shiyu Wang; Qingsong Wen; Tom Hartvigsen; Fei Wang; B. Aditya Prakash (CoRR, 2025)