| Random infinite tree and dependent Poisson diffusion process for nonparametric Bayesian modeling in multiple object tracking B Moraffah, A Papandreou-Suppappola ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 22 | 2019 |
| Dependent Dirichlet process modeling and identity learning for multiple object tracking B Moraffah, A Papandreou-Suppappola 2018 52nd Asilomar Conference on Signals, Systems, and Computers, 1762-1766, 2018 | 21 | 2018 |
| Inference for multiple object tracking: A Bayesian nonparametric approach B Moraffah arXiv preprint arXiv:1909.06984, 2019 | 14 | 2019 |
| Use of hierarchical Dirichlet processes to integrate dependent observations from multiple disparate sensors for tracking B Moraffah, C Brito, B Venkatesh, A Papandreou-Suppappola 2019 22th International Conference on Information Fusion (FUSION), 1-7, 2019 | 14 | 2019 |
| Nonparametric Bayesian methods and the dependent Pitman-Yor process for modeling evolution in multiple object tracking B Moraffah, A Papandreou-Suppappola, M Rangaswamy 2019 22th International Conference on Information Fusion (FUSION), 1-6, 2019 | 13 | 2019 |
| Information-theoretic private interactive mechanism B Moraffah, L Sankar 2015 53rd Annual Allerton Conference on Communication, Control, and …, 2015 | 13 | 2015 |
| Causal adversarial network for learning conditional and interventional distributions R Moraffah, B Moraffah, M Karami, A Raglin, H Liu arXiv preprint arXiv:2008.11376, 2020 | 12 | 2020 |
| Tracking multiple objects with multimodal dependent measurements: Bayesian nonparametric modeling B Moraffah, C Brito, B Venkatesh, A Papandreou-Suppappola 2019 53rd Asilomar Conference on Signals, Systems, and Computers, 1847-1851, 2019 | 10 | 2019 |
| Bayesian nonparametric modeling for predicting dynamic dependencies in multiple object tracking B Moraffah, A Papandreou-Suppappola Sensors 22 (1), 388, 2022 | 8 | 2022 |
| Bayesian nonparametric modeling and inference for multiple object tracking B Moraffah Arizona State University, 2019 | 8 | 2019 |
| Can: A causal adversarial network for learning observational and interventional distributions R Moraffah, B Moraffah, M Karami, A Raglin, H Liu arXiv preprint arXiv:2008.11376, 2020 | 7 | 2020 |
| Bradycardia prediction in preterm infants using nonparametric kernel density estimation S Das, B Moraffah, A Banerjee, SKS Gupta, A Papandreou-Suppappola 2019 53rd Asilomar Conference on Signals, Systems, and Computers, 1309-1313, 2019 | 7 | 2019 |
| Privacy-guaranteed two-agent interactions using information-theoretic mechanisms B Moraffah, L Sankar IEEE Transactions on Information Forensics and Security 12 (9), 2168-2183, 2017 | 5 | 2017 |
| Metric-bayes: Measurements estimation for tracking in high clutter using bayesian nonparametrics B Moraffah, C Richmond, R Moraffah, A Papandreou-Suppappola 2020 54th Asilomar Conference on Signals, Systems, and Computers, 1518-1522, 2020 | 3 | 2020 |
| Sequential Bayesian inference using stochastic models of gene regulatory networks N Vélez-Cruz, B Moraffah, A Papandreou-Suppappola 2021 55th Asilomar Conference on Signals, Systems, and Computers, 568-572, 2021 | 2 | 2021 |
| Use of bayesian nonparametric methods for estimating the measurements in high clutter B Moraffah, C Richmond, R Moraffah, A Papandreou-Suppappola arXiv preprint arXiv:2012.09785, 2020 | 2 | 2020 |
| Bayesian estimation for tracking multiple objects: Sequential monte carlo methods B Moraffah | 1 | 2019 |
| Introduction to Machine Learning: A Review B Moraffah arXiv preprint arXiv:1007.0296, 2019 | 1 | 2019 |
| Bayesian Nonparametrics: An Alternative to Deep Learning B Moraffah arXiv preprint arXiv:2404.00085, 2024 | | 2024 |
| Interference Mitigation in Spectrum Sharing Environments Using Time-Frequency Processing and Feature Clustering Y Zhang, B Moraffah, A Papandreou-Suppappola 2022 56th Asilomar Conference on Signals, Systems, and Computers, 514-518, 2022 | | 2022 |
