Publications

Conference Proceedings

1. Normalizing Flow for Two-Sample Hypothesis Testing: Improved Uncertainty Representation but Not Necessarily More Power
   Parth Paritosh, James Z. Hare and Lance Kaplan
   Accepted at 2026 International Conference on Information Fusion (ICIF)

2. The Effect of the Prior on Asymptotic Performance of Uncertain Naive Bayesian Networks
   Lance Kaplan, James Z. Hare and Parth Paritosh
   2025 International Conference on Information Fusion (ICIF) [Xplore] [DOI]

3. Privacy-Preserving Convergent Dynamic Average Consensus via State Decomposition
   Parth Paritosh and Lance Kaplan
   2025 IEEE Statistical Signal Processing Workshop (SSP) [Xplore] [DOI]

4. Distributed Bayesian Estimation of Continuous Variables Over Time-Varying Directed Networks
   Parth Paritosh, Nikolay Atanasov and Sonia Martinez
   2022 IEEE 61st Conference on Decision and Control (CDC) [PDF] [Xplore] [Code] [Slides] [DOI]

5. Marginal density averaging for distributed node localization from local edge measurements
   Parth Paritosh, Nikolay Atanasov and Sonia Martinez
   2020 IEEE 59th Conference on Decision and Control (CDC) [Xplore] [PDF] [Slides] [DOI]

6. Hypothesis Assignment and Partial Likelihood Averaging for Cooperative Estimation
   Parth Paritosh, Nikolay Atanasov and Sonia Martinez
   2019 IEEE 58th Conference on Decision and Control (CDC) [Xplore] [PDF] [Slides] [DOI]

Journal Articles

1. Privacy-Preserving Distributed Maximum Likelihood Estimation via State Decomposition.
   Parth Paritosh and Lance Kaplan
   IEEE Transactions on Signal Processing, 2026 [PDF] [DOI]

2. Distributed Bayesian Estimation in Sensor Networks: Consensus on Marginal Densities.
   Parth Paritosh, Nikolay Atanasov and Sonia Martinez
   IEEE Transactions on Network Science and Engineering, 2025 [arXiv] [PDF] [Xplore] [DOI]

3. Distributed Variational Inference for Online Supervised Learning
   Parth Paritosh, Nikolay Atanasov and Sonia Martinez
   IEEE Transactions on Control of Network Systems, 2025 [PDF] [arXiv] [Code] [Xplore] [DOI]
   Presented at 2025 IEEE Conference on Decision and Control (CDC) [Slides]

4. Distributed Bayesian Estimation of Continuous Variables Over Time-Varying Directed Networks
   Parth Paritosh, Nikolay Atanasov and Sonia Martinez
   IEEE Control Systems Letters, 2022 [PDF] [Code Capsule] [Slides] [DOI]

5. Model predictive control under forecast uncertainty for optimal operation of buildings
   with integrated solar systems
   Xiaoqi Liu, Parth Paritosh, Nimish M Awalgaonkar, Ilias Bilionis and Panagiota Karava
   Solar Energy, 2018 [PDF] [DOI]

6. A game theory based land layout optimization of cities using genetic algorithm
   Parth Paritosh, Bhaben Kalita and Deepak Sharma
   International Journal of Management Science and Engineering Management, 2018 [Link] [DOI]

Thesis

1. Scalable and Efficient Bayesian Algorithms for Distributed Estimation and Inference
   Doctoral Thesis [Link] [Slides]

2. Gaussian Process Dynamical Models for Designing Multi-Stage Manufacturing Processes
   Master's Thesis [Link] [Slides]