| MOMENT: A Family of Open Time-series Foundation Models M Goswami, K Szafer, A Choudhry, Y Cai, S Li, A Dubrawski International Conference on Machine Learning (ICML) 2024, 2024 | 118 | 2024 |
| Are you paying attention? Detecting distracted driving in real-time M Leekha, M Goswami, RR Shah, Y Yin, R Zimmermann 2019 IEEE Fifth International Conference on Multimedia Big Data (BigMM), 171-180, 2019 | 53 | 2019 |
| Unsupervised model selection for time-series anomaly detection M Goswami, C Challu, L Callot, L Minorics, A Kan International Conference on Learning Representations (ICLR) 2023, 2022 | 47 | 2022 |
| Counterfactual phenotyping with censored time-to-events C Nagpal, M Goswami, K Dufendach, A Dubrawski Proceedings of the 28th ACM SIGKDD conference on knowledge discovery and …, 2022 | 29 | 2022 |
| A binary PSO approach for improving the performance of wireless sensor networks A Kaushik, M Goswami, M Manuja, S Indu, D Gupta Wireless Personal Communications 113, 263-297, 2020 | 25 | 2020 |
| Weak supervision for affordable modeling of electrocardiogram data M Goswami, B Boecking, A Dubrawski AMIA Annual Symposium Proceedings 2021, 536, 2022 | 17 | 2022 |
| Toward learning at scale in developing countries: lessons from the global learning XPRIZE field study AA McReynolds, SP Naderzad, M Goswami, J Mostow Proceedings of the Seventh ACM Conference on Learning@ Scale, 175-183, 2020 | 13 | 2020 |
| Towards social & engaging peer learning: Predicting backchanneling and disengagement in children M Goswami, M Manuja, M Leekha arXiv preprint arXiv:2007.11346, 2020 | 12 | 2020 |
| Classifying unstructured clinical notes via automatic weak supervision C Gao, M Goswami, J Chen, A Dubrawski Machine Learning for Healthcare Conference, 673-690, 2022 | 11 | 2022 |
| Discriminating cognitive disequilibrium and flow in problem solving: A semi-supervised approach using involuntary dynamic behavioral signals M Goswami, L Chen, A Dubrawski Proceedings of the AAAI Conference on Artificial Intelligence 34 (01), 420-427, 2020 | 11 | 2020 |
| Learning graph neural networks for multivariate time series anomaly detection S Ray, S Lakdawala, M Goswami, C Gao arXiv preprint arXiv:2111.08082, 2021 | 10 | 2021 |
| What makes a better companion? towards social & engaging peer learning R Jindal, M Leekha, M Manuja, M Goswami ECAI 2020, 482-489, 2020 | 9 | 2020 |
| A multi-task approach to open domain suggestion mining using language model for text over-sampling M Leekha, M Goswami, M Jain 42nd European Conference on IR Research (ECIR) 2020, Lisbon, Portugal, 223-229, 2020 | 9 | 2020 |
| What’s most broken? design and evaluation of a tool to guide improvement of an intelligent tutor S Mian, M Goswami, J Mostow Artificial Intelligence in Education (AIED) 2019, 283-295, 2019 | 9 | 2019 |
| Aqua: A benchmarking tool for label quality assessment M Goswami, V Sanil, A Choudhry, A Srinivasan, C Udompanyawit, ... Advances in Neural Information Processing Systems 36, 79792-79807, 2023 | 8 | 2023 |
| Detecting intrusive transactions in databases using partially-ordered sequential rule mining and fractional-distance based anomaly detection I Singh, M Manuja, R Mathur, M Goswami International Journal of Intelligent Engineering Informatics 8 (2), 138-171, 2020 | 8 | 2020 |
| Jolt: Jointly learned representations of language and time-series Y Cai, M Goswami, A Choudhry, A Srinivasan, A Dubrawski Deep Generative Models for Health Workshop NeurIPS 2023, 2023 | 6 | 2023 |
| Weakly supervised classification of vital sign alerts as real or artifact A Dey, M Goswami, JH Yoon, G Clermont, M Pinsky, M Hravnak, ... AMIA Annual Symposium Proceedings 2022, 405, 2023 | 3 | 2023 |
| A multi-task approach to open domain suggestion mining (student abstract) M Jain, M Leekha, M Goswami Proceedings of the AAAI Conference on Artificial Intelligence 34 (10), 13817 …, 2020 | 3 | 2020 |
| Detecting Patterns of Physiological Response to Hemodynamic Stress via Unsupervised Deep Learning C Gao, F Falck, M Goswami, A Wertz, MR Pinsky, A Dubrawski Machine Learning for Health (ML4H), NeurIPS 2019 (Extended Abstract), 2019 | 3 | 2019 |
Artur DubrawskiCarnegie Mellon UniversityVerified email at cs.cmu.edu
