| Spatiotemporal attention for multivariate time series prediction and interpretation T Gangopadhyay, SY Tan, Z Jiang, R Meng, S Sarkar ICASSP 2021-2021 IEEE international conference on acoustics, speech and …, 2021 | 49 | 2021 |
| Cross-gradient aggregation for decentralized learning from non-iid data Y Esfandiari, SY Tan, Z Jiang, A Balu, E Herron, C Hegde, S Sarkar International conference on machine learning, 3036-3046, 2021 | 42 | 2021 |
| Temporal attention and stacked LSTMs for multivariate time series prediction T Gangopadhyay, SY Tan, G Huang, S Sarkar NeurIPS Workshop on Modeling and Decision-Making in the Spatiotemporal Domain, 2018 | 23 | 2018 |
| Decentralized deep learning using momentum-accelerated consensus A Balu, Z Jiang, SY Tan, C Hedge, YM Lee, S Sarkar ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and …, 2021 | 22 | 2021 |
| Multimodal sensor fusion framework for residential building occupancy detection SY Tan, M Jacoby, H Saha, A Florita, G Henze, S Sarkar Energy and buildings 258, 111828, 2022 | 18 | 2022 |
| Battery-free camera occupancy detection system A Saffari, SY Tan, M Katanbaf, H Saha, JR Smith, S Sarkar Proceedings of the 5th International Workshop on Embedded and Mobile Deep …, 2021 | 18 | 2021 |
| A high-fidelity residential building occupancy detection dataset M Jacoby, SY Tan, G Henze, S Sarkar Scientific Data 8 (1), 280, 2021 | 17 | 2021 |
| A flexible framework for building occupancy detection using spatiotemporal pattern networks SY Tan, H Saha, AR Florita, GP Henze, S Sarkar 2019 American Control Conference (ACC), 5884-5889, 2019 | 8 | 2019 |
| Granger Causality Based Hierarchical Time Series Clustering for State Estimation SY Tan, H Saha, M Jacoby, G Henze, S Sarkar IFAC-PapersOnLine 53 (2), 524-529, 2020 | 7 | 2020 |
| Interpretable deep learning for monitoring combustion instability T Gangopadhyay, SY Tan, A LoCurto, JB Michael, S Sarkar IFAC-PapersOnLine 53 (2), 832-837, 2020 | 7 | 2020 |
| Interpretable deep attention model for multivariate time series prediction in building energy systems T Gangopadhyay, SY Tan, Z Jiang, S Sarkar Dynamic Data Driven Applications Systems: Third International Conference …, 2020 | 7 | 2020 |
| Few-shot deep learning for AFM force curve characterization of single-molecule interactions JR Waite, SY Tan, H Saha, S Sarkar, A Sarkar Patterns 4 (1), 2023 | 6 | 2023 |
| Whisper: wireless home identification and sensing platform for energy reduction M Jacoby, SY Tan, M Katanbaf, A Saffari, H Saha, Z Kapetanovic, ... Journal of Sensor and Actuator Networks 10 (4), 71, 2021 | 6 | 2021 |
| An explainable framework using deep attention models for sequential data in combustion systems T Gangopadhyay, SY Tan, A Locurto, JB Michael, S Sarkar NeurIPS 2019 Workshop on Machine Learning and the Physical Sciences. NeurIPS, 2019 | 6 | 2019 |
| MDPGT: momentum-based decentralized policy gradient tracking Z Jiang, XY Lee, SY Tan, KL Tan, A Balu, YM Lee, C Hegde, S Sarkar Proceedings of the AAAI Conference on Artificial Intelligence 36 (9), 9377-9385, 2022 | 5 | 2022 |
| Few shot clustering for indoor occupancy detection with extremely low quality images from battery free cameras H Saha Iowa State University, 2021 | 4 | 2021 |
| On Higher-order Moments in Adam Z Jiang, A Balu, SY Tan, YM Lee, C Hegde, S Sarkar arXiv preprint arXiv:1910.06878, 2019 | 3 | 2019 |
| Learning State Switching for Multi-sensor Integration H Saha, SY Tan, Z Jiang, S Sarkar 2019 Sixth Indian Control Conference (ICC), 232-237, 2019 | 2 | 2019 |
| Active shooter detection and robust tracking utilizing supplemental synthetic data JR Waite, J Feng, R Tavassoli, L Harris, SY Tan, S Chakraborty, S Sarkar arXiv preprint arXiv:2309.03381, 2023 | | 2023 |
| Multimodal sensor fusion and multisource distributed learning in cyber-physical systems SY Tan | | 2022 |
Soumik SarkarDirector, Translational AI Center, Professor, Iowa State UniversityVerified email at iastate.edu
