Prakash, B. Aditya

22 publications

UAI 2025 DF$^2$: Distribution-Free Decision-Focused Learning Lingkai Kong, Wenhao Mu, Jiaming Cui, Yuchen Zhuang, B. Aditya Prakash, Bo Dai, Chao Zhang

ICML 2025 EARTH: Epidemiology-Aware Neural ODE with Continuous Disease Transmission Graph Guancheng Wan, Zewen Liu, Xiaojun Shan, Max Sy Lau, B. Aditya Prakash, Wei Jin

IJCAI 2024 A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation Mohammad Hashemi, Shengbo Gong, Juntong Ni, Wenqi Fan, B. Aditya Prakash, Wei Jin

NeurIPS 2024 Large Pre-Trained Time Series Models for Cross-Domain Time Series Analysis Tasks Harshavardhan Kamarthi, B. Aditya Prakash

ICLR 2024 PINNsFormer: A Transformer-Based Framework for Physics-Informed Neural Networks Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash

NeurIPS 2024 Time-MMD: 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

ICML 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

ICML 2023 Autoregressive Diffusion Model for Graph Generation Lingkai Kong, Jiaming Cui, Haotian Sun, Yuchen Zhuang, B. Aditya Prakash, Chao Zhang

AAAI 2023 Detecting Sources of Healthcare Associated Infections Hankyu Jang, Andrew Fu, Jiaming Cui, Methun Kamruzzaman, B. Aditya Prakash, Anil Vullikanti, Bijaya Adhikari, Sriram V. Pemmaraju

AAAI 2023 EINNs: Epidemiologically-Informed Neural Networks Alexander Rodríguez, Jiaming Cui, Naren Ramakrishnan, Bijaya Adhikari, B. Aditya Prakash

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

ICMLW 2022 Differentiable Agent-Based Epidemiological Modeling for End-to-End Learning Ayush Chopra, Alexander Rodríguez, Jayakumar Subramanian, Balaji Krishnamurthy, B. Aditya Prakash, Ramesh Raskar

NeurIPS 2022 End-to-End Stochastic Optimization with Energy-Based Model Lingkai Kong, Jiaming Cui, Yuchen Zhuang, Rui Feng, B. Aditya Prakash, Chao Zhang

AAAI 2022 Provable Sensor Sets for Epidemic Detection over Networks with Minimum Delay Jack Heavey, Jiaming Cui, Chen Chen, B. Aditya Prakash, Anil Vullikanti

AAAI 2021 DeepCOVID: An Operational Deep Learning-Driven Framework for Explainable Real-Time COVID-19 Forecasting Alexander Rodríguez, Anika Tabassum, Jiaming Cui, Jiajia Xie, Javen Ho, Pulak Agarwal, Bijaya Adhikari, B. Aditya Prakash

AAAI 2021 Steering a Historical Disease Forecasting Model Under a Pandemic: Case of Flu and COVID-19 Alexander Rodríguez, Nikhil Muralidhar, Bijaya Adhikari, Anika Tabassum, Naren Ramakrishnan, B. Aditya Prakash

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

NeurIPSW 2020 NetReAct: Interactive Learning for Network Summarization Sorour E. Amiri, Bijaya Adhikari, John Wenskovitch, Alexander Rodriguez, Michelle Dowling, Christopher North, B. Aditya Prakash

AAAI 2018 Automatic Segmentation of Data Sequences Liangzhe Chen, Sorour E. Amiri, B. Aditya Prakash

AAAI 2017 SnapNETS: Automatic Segmentation of Network Sequences with Node Labels Sorour E. Amiri, Liangzhe Chen, B. Aditya Prakash

ICML 2011 Time Series Clustering: Complex Is Simpler! Lei Li, B. Aditya Prakash

ECML-PKDD 2010 Virus Propagation on Time-Varying Networks: Theory and Immunization Algorithms B. Aditya Prakash, Hanghang Tong, Nicholas Valler, Michalis Faloutsos, Christos Faloutsos