Publications

Preprints

1. Consistency-based Black-box Uncertainty Quantification for Text-to-SQL.
   Bhattacharjya, D., Ganesan, B., Glass, M., Lee, J. , Marinescu. R., Mirylenka, K., & Shou, X..
   Under Review
2. Self-Supervised Contrastive Pre-Training for Multivariate Point Processes.
   Shou,X., Subramianian D., Bhattacharjya, D., Gao, T., Bennett, K.P.
   ArXiv preprint, 2402.00987v1

Journal Papers

1. [Methods] Supervised mixture of expert models for population health (Supervised Mixture of Bernoulli).
   Xiao Shou, Mavroudeas, G., Magdon-Ismail, M., Figueroa, J., Kuruzovich, J. N., & Bennett, K. P.
   Elsevier Methods, 2020

Conference Papers

1. [DASFAA'25] Less is More: Efficient Weight “Farcasting” with 1-Layer Neural Network.
   Shou,X., Bhattacharjya, D., Ding, Y.,Zhao, C., Li, R. & Gao, J.
   In Proceedings of International Conference on Database Systems for Advanced Applications (full,Oral), 2025
2. [AAAI'25] Architecture-Aware Learning Curve Extrapolation via Graph Ordinary Differential Equation.
   Ding, Y., Huang, Z., Shou, X., Guo,Y., Sun,Y., & Gao, J.
   In Proceedings of AAAI Conference on Artificial Intelligence (full paper), 2025
3. [NeurIPS'23] Pairwise Causality Guided Transformers for Event Sequences.
   Shou, X. , Gao, T, Subramanian, D., Bhattacharjya, D. & Bennett, K. P.
   In Proceedings of Conference on Neural Information Processing Systems (full paper), 2023
4. [ICML'23] Probabilistic Attention-to-Influence Neural Models for Event Sequences.
   Shou, X. , Bhattacharjya, D. Gao, T., Subramanian, D., Hassanzadeh, O., & Bennett, K. P.
   In Proceedings of International Conference on Machine Learning (full paper), 2023
5. [AAAI'23] Score-Based Learning of Graphical Event Models with Background Knowledge Augmentation.
   Bhattacharjya D., Gao T., Subramanian, D., Shou, X.
   In Proceedings of AAAI Conference on Artificial Intelligence (full paper), 2023
6. [AAAI'23] Concurrent Multi-Label Prediction in Event Streams.
   Shou, X. , Gao, T., Subramanian, D., Bhattacharjya, D. & Bennett, K. P.
   In Proceedings of AAAI Conference on Artificial Intelligence (full paper, Oral ), 2023
7. [CLeaR'23] Influence-Aware Attention for Multi-dimensional Temporal Point Process.
   Shou, X. , Gao, T., Subramanian, D., Bhattacharjya, D. & Bennett, K. P.
   In Proceedings of Causal Learning and Reasoning Conference (full paper ), 2023
8. [ICKG'22] HMM-Boost: Improved Time Series State Prediction Via Supervised Hidden Markov Models: Case Studies in Epileptic Seizure and Complex Care Management.
   Mavroudeas, G., Magdon-Ismail M., Shou, X. , and Bennett K. P.
   In Proceedings of IEEE International Conference on Knowledge Graph (full paper ), 2022
9. [NeurIPS'21] Causal Inference for Event Pairs in Multivariate Point Processes.
   Gao, T., Subramanian, D., Bhattacharjya, D., Shou, X., Mattei, N., & Bennett, K.
   In Proceedings of Conference on Neural Information Processing Systems (full paper), 2021.
10. [ACM BCB'21] Match2: hybrid self-organizing map and deep learning strategies for treatment effect estimation.
    Shou, X. , Gao, T., Subramanian, D., & Bennett, K. P.
    In Proceedings of ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (full paper, Best Student Paper Award), 2021.
11. [IEEE BIBM'21] Predictive Modeling for Complex Care Management.
    Mavroudeas, G., Neehal, N., Shou, X. , Magdon-Ismail, M., Kuruzovich, J., and Bennett K. P.
    In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (full paper ), 2021.
12. [IEEE BIBM'20] Supervised mixture of expert models for population health (Supervised Mixture of Gaussians).
    Shou, X. , Mavroudeas, G., New, A., Arhin, K., Kuruzovich, J. N., Magdon-Ismail, M., & Bennett, K. P.
    In Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (full paper), 2020.

Workshop Papers

1. [NeurIPS'24-W] Consistency-based Black-box Uncertainty Quantification for Text-to-SQL, Bhattacharjya,D., Ganesan, B., Glass, M., Lee,J., Marinescu. R., Mirylenka, K., Shou,X..
   NeurIPS Workshop on Statistical Foundations of LLMs and Foundation Models, 2024
2. [ICDM'22-W] HMM-Boost: Improved Time Series State Prediction Via Supervised Hidden Markov Models: Case Studies in Epileptic Seizure and Complex Care Management.
   Mavroudeas, G., Magdon-Ismail, M., Shou,X. & Bennett, K.P.
   ICDM Workshop on Data Mining in Biomedical Informatics and Healthcare , 2022