Bahman Moraffah - Publications
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Preprints
CAN: A Causal Adversarial Network for Learning Observational and Interventional Distributions
Raha Moraffah, Bahman Moraffah, Adrienne Raglin, Masoure Karimi, Haun Liu
[ arXiv ][ supplementary material ][ data ][ code ] [ bibtex ]
Publications
Interference Mitigation in Spectrum Sharing Environments Using Time-Frequency Processing and Feature Clustering
Yiming Zhang, Bahman Moraffah,and Antonia Papandreou-Suppappola
54th Annual Asilomar Conference on Signals, Systems, and Computers, 2022
[ pdf ][ arXiv ] [ code ] [ bibtex ]
Switching Langevin Dynamics for Gene Regulatory Networks
Nayely Velez-Cruz, Bahman Moraffah,and Antonia Papandreou-Suppappola
The International Conference on Acoustics, Speech, & Signal Processing (ICASSP), 2022
[ pdf ][ arXiv ] [ code ] [ bibtex ]
Bayesian nonparametric modeling for predicting dynamic dependencies in multiple object tracking
Nayely Velez-Cruz, Bahman Moraffah,and Antonia Papandreou-Suppappola
Sensor, MDPI, 2022
[ pdf ][ arXiv ] [ code ] [ bibtex ]
Complete Recipe for Bayesian Knowledge Transfer: Object Tracking
Bahman Moraffah, Antonia Papandreou-Suppappola
54th Annual Asilomar Conference on Signals, Systems, and Computers, 2022
[ pdf ][ arXiv ] [ code ] [ bibtex ]
Bayesian Nonparametric Derivation of Spawning in Multi-Object Tracking: from Association to Tracking
Bahman Moraffah
53rd Annual Asilomar Conference on Signals, Systems, and Computers, 2021
[ pdf ][ arXiv ] [ code ] [ bibtex ]
Sequential Bayesian Inference Using Stochastic Models of Gene Regulatory Networks
Nayely Velez-Cruz, Bahman Moraffah,and Antonia Papandreou-Suppappola
53rd Annual Asilomar Conference on Signals, Systems, and Computers, 2021
[ pdf ][ arXiv ] [ code ] [ bibtex ]
METRIC-Bayes: Measurements Estimation for Tracking in High Clutter using Bayesian Nonparametrics
Bahman Moraffah, Christ Richmond, Raha Moraffah, and Antonia Papandreou-Suppappola
54th Annual Asilomar Conference on Signals, Systems, and Computers, 2020
[ pdf ][ arXiv ] [ code ] [ bibtex ]
Tracking Multiple Objects with Multimodal Dependent Measurements: Bayesian Nonparametric Modeling
Bahman Moraffah, Cesar Brito, Bindya Venkatesh, Antonia Papandreou-Suppappola
53rd Annual Asilomar Conference on Signals, Systems, and Computers, 2019
[ pdf ][ code ][ poster ][ bibtex ]
Bradycardia Prediction in Preterm Infants Using Nonparametric Kernel Density Estimation
Subhasish Das, Bahman Moraffah, Sandeep K.S. Gupta, Antonia Papandreou-Suppappola
53rd Annual Asilomar Conference on Signals, Systems, and Computers, 2019
[ pdf ][ code ][ poster ][ bibtex ]
Nonparametric Bayesian Methods and the Dependent Pitman-Yor Process for Modeling Evolution in Multiple State Priors
Bahman Moraffah, Muralidhar Rangaswamy, Antonia Papandreou-Suppappola
22nd International Conference on Information Fusion, 2019
[ pdf ][ code ][ slides ][ bibtex ]
Use of Hierarchical Dirichlet Processes to Integrate Dependent Observations from Multiple Disparate Sensors for Tracking
Bahman Moraffah, Cesar Brito, Bindya Venkatesh, Antonia Papandreou-Suppappola
22nd International Conference on Information Fusion, 2019
[ pdf ][ code ][slides][ bibtex ]
Dependent Dirichlet Process Modeling and Identity Learning for Multiple Object Tracking
Bahman Moraffah, Antonia Papandreou-Suppappola
52nd Annual Asilomar Conference on Signals, Systems, and Computers, 1762–1766, 2018
[ pdf ][ code ][poster][ bibtex ]
Privacy-Guaranteed Two-Agent Interactions Using Information-Theoretic Mechanisms
Bahman Moraffah, Lalitha Sankar
IEEE Trans. Information Forensics and Security,12(9): 2168-2183, 2017
[ pdf ][ arXiv ][ bibtex ]
Information-Theoretic Private Interactive Mechanism
Bahman Moraffah, Lalitha Sankar
53rd Annual Allerton Conference on Communication, Control, and Computing, No. 89, 2015
[ pdf ] [slides] [ bibtex ]
Books
Probability, Statistics, and Random Processes with Applications in Learning Theory
Bahman Moraffah
Expected 2021
Bayesian Modeling and Inference: A Bayesian Approach to Machine Learning
Bahman Moraffah
Expected 2022
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