| Boosting for postpartum depression prediction S Natarajan, A Prabhakar, N Ramanan, A Bagilone, K Siek, K Connelly 2017 IEEE/ACM International Conference on Connected Health: Applications …, 2017 | 37 | 2017 |
| Causal learning from predictive modeling for observational data N Ramanan, S Natarajan Frontiers in big Data 3, 535976, 2020 | 16 | 2020 |
| Structure Learning for Relational Logistic Regression: An Ensemble Approach N Ramanan, G Kunapuli, T Khot, B Fatemi, SM Kazemi, D Poole, ... arXiv preprint arXiv:1808.02123, 2018 | 16 | 2018 |
| Boosted embeddings for time-series forecasting SR Karingula, N Ramanan, R Tahmasbi, M Amjadi, D Jung, R Si, ... International Conference on Machine Learning, Optimization, and Data Science …, 2021 | 15 | 2021 |
| Whom Should I Perform the Lab Test on Next? An Active Feature Elicitation Approach S Natarajan, S Das, N Ramanan, G Kunapuli, P Radivojac IJCAI, 2018 | 11 | 2018 |
| Interactive transfer learning in relational domains R Kumaraswamy, N Ramanan, P Odom, S Natarajan KI-Künstliche Intelligenz 34, 181-192, 2020 | 6 | 2020 |
| Few-shot induction of generalized logical concepts via human guidance M Das, N Ramanan, JR Doppa, S Natarajan Frontiers in Robotics and AI 7, 122, 2020 | 4 | 2020 |
| Discriminative non-parametric learning of arithmetic circuits N Ramanan, M Das, K Kersting, S Natarajan International Conference on Probabilistic Graphical Models, 353-364, 2020 | 3 | 2020 |
| Discriminative boosted Bayes networks for learning multiple cardiovascular procedures N Ramanan, S Yang, S Grannis, S Natarajan 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2017 | 3 | 2017 |
| Time Series Anomaly Detection with label-free Model Selection D Jung, N Ramanan, M Amjadi, SR Karingula, J Taylor, CN Coelho Jr arXiv preprint arXiv:2106.07473, 2021 | 2 | 2021 |
| Work-in-Progress: Ensemble Causal Learning for Modeling Post-partum Depression N Ramanan, S Natarajan Palo Alto, CA, 2019 | 2 | 2019 |
| Real-time drift detection on time-series data N Ramanan, R Tahmasbi, M Sayer, D Jung, S Hemachandran, ... arXiv preprint arXiv:2110.06383, 2021 | 1 | 2021 |
| Active feature elicitation: An unified framework S Das, N Ramanan, G Kunapuli, P Radivojac, S Natarajan Frontiers in Artificial Intelligence 6, 1029943, 2023 | | 2023 |
| Active Feature Acquisition via Human Interaction in Relational domains N Ramanan, P Odom, K Kersting, S Natarajan Proceedings of the 6th Joint International Conference on Data Science …, 2023 | | 2023 |
| Contrastive Credibility Propagation for Reliable Semi-Supervised Learning B Kutt, P Toman, X Mignot, SR Chhetri, S Huang, N Ramanan, M Du, ... arXiv preprint arXiv:2211.09929, 2022 | | 2022 |
| Log2NS: Enhancing Deep Learning Based Analysis of Logs With Formal to Prevent Survivorship Bias C Thimmisetty, P Tiwari, DG de la Iglesia, N Ramanan, M Sayer, ... arXiv preprint arXiv:2105.14149, 2021 | | 2021 |
| Boosted Embeddings for Time Series Forecasting S Rao Karingula, N Ramanan, R Tahmasbi, M Amjadi, D Jung, R Si, ... arXiv e-prints, arXiv: 2104.04781, 2021 | | 2021 |
| Efficient and Effective Structure Learning of Graphical Models N Ramanan The University of Texas at Dallas, 2020 | | 2020 |
| Discriminative boosted Bayes networks for learning multiple cardiovascular procedures Download PDF N Ramanan, S Yang, S Grannis, S Natarajan | | |
| Probabilistic Models for Cardiovascular Events KM Sanders, RM Long, N Ramanan, S Natarajan | | |
Sriraam NatarajanUniversity of Texas at DallasVerified email at utdallas.edu
