Harshavardhan Kamarthi

According to our database, Harshavardhan Kamarthi authored at least 21 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning Graph Structures and Uncertainty for Accurate and Calibrated Time-series Forecasting.

Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash

CoRR, 2024

Time-MMD: A New Multi-Domain Multimodal Dataset for Time Series Analysis.

Haoxin Liu, Shangqing Xu, Zhiyuan Zhao, Lingkai Kong, Harshavardhan Kamarthi, Aditya B. Sasanur, Megha Sharma, Jiaming Cui, Qingsong Wen, Chao Zhang, B. Aditya Prakash

CoRR, 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

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Time-Series Forecasting for Out-of-Distribution Generalization Using Invariant Learning.

Haoxin Liu, Harshavardhan Kamarthi, Lingkai Kong, Zhiyuan Zhao, Chao Zhang, B. Aditya Prakash

Proceedings of the Forty-first International Conference on Machine Learning, 2024

LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting.

Haoxin Liu, Zhiyuan Zhao, Jindong Wang, Harshavardhan Kamarthi, B. Aditya Prakash

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Large Pre-trained time series models for cross-domain Time series analysis tasks.

Harshavardhan Kamarthi, B. Aditya Prakash

CoRR, 2023

PEMS: Pre-trained Epidemic Time-series Models.

Harshavardhan Kamarthi, B. Aditya Prakash

CoRR, 2023

Uncertainty Quantification in Deep Learning.

Lingkai Kong, Harshavardhan Kamarthi, Peng Chen, B. Aditya Prakash, Chao Zhang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting.

Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

2022

Data-Centric Epidemic Forecasting: A Survey.

Alexander Rodríguez, Harshavardhan Kamarthi, Pulak Agarwal, Javen Ho, Mira Patel, Suchet Sapre, B. Aditya Prakash

CoRR, 2022

PROFHIT: Probabilistic Robust Forecasting for Hierarchical Time-series.

Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash

CoRR, 2022

CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting.

Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Epidemic Forecasting with a Data-Centric Lens.

Alexander Rodríguez, Harshavardhan Kamarthi, B. Aditya Prakash

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future.

Harshavardhan Kamarthi, Alexander Rodríguez, B. Aditya Prakash

Proceedings of the Tenth International Conference on Learning Representations, 2022

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, Balaraman Ravindran, Milind Tambe

CoRR, 2021

When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting.

Harshavardhan Kamarthi, Lingkai Kong, Alexander Rodríguez, Chao Zhang, B. Aditya Prakash

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Reinforcement Learning for Unified Allocation and Patrolling in Signaling Games with Uncertainty.

Aravind Venugopal, Elizabeth Bondi, Harshavardhan Kamarthi, Keval Dholakia, Balaraman Ravindran, Milind Tambe

Proceedings of the AAMAS '21: 20th International Conference on Autonomous Agents and Multiagent Systems, 2021

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

Influence Maximization in Unknown Social Networks: Learning Policies for Effective Graph Sampling.

Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe

Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019

Integrating Lexical Knowledge in Word Embeddings using Sprinkling and Retrofitting.

Aakash Srinivasan, Harshavardhan Kamarthi, Devi Ganesan, Sutanu Chakraborti

CoRR, 2019

Learning policies for Social network discovery with Reinforcement learning.

Harshavardhan Kamarthi, Priyesh Vijayan, Bryan Wilder, Balaraman Ravindran, Milind Tambe

CoRR, 2019