Vepakomma, P., Balla, J., Raskar, R., "Splintering with distributions: A stochastic decoy scheme for private computation." 6 Jul 2020.
Alex Berke, Michiel Bakker, Praneeth Vepakomma, Kent Larson, Alex `Sandy' Pentland. (March 31 2020). "Assessing Disease Exposure Risk with Location Data: A Proposal for Cryptographic Preservation of Privacy." Retrieved from https://arxiv.org/pdf/2003.14412
Peter Kairouz, H. Brendan McMahan, et al. "Advances and Open Problems in Federated Learning." arXiv:1912.04977 [cs.LG] 10 Dec 2019.
Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree KalpathyCramer, and Ramesh Raskar. In NeurIPS Workshop on Robust AI in Financial Services: Data, Fairness, Explainability, Trustworthiness, and Privacy, 2019
Indu Ilanchezian, Praneeth Vepakomma, Abhishek Singh, Otkrist Gupta, GN Prasanna, Ramesh Raskar
Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree Kalpathy-Cramer, Ramesh Raskar. In NeurIPS Workshop on Machine learning for the Developing World (ML4D), 2019
Praneeth Vepakomma, et al. "Detailed comparison of communication efficiency of split learning and federated learning." arXiv:1909.09145v1 [cs.LG] 18 Sep 2019.
Ramesh Raskar, Praneeth Vepakomma, Tristan Swedish, Aalekh Sharan. Data Markets to support AI for All: Pricing, Valuation and Governance, arXiv:1905.06462 (2019).
Sai Sri Sathya, Praneeth Vepakomma, Ramesh Raskar, Ranjan Ramachandra, Santanu Bhattacharya. arXiv:1812.02428
Praneeth Vepakomma, et al. "Split learning for health: Distributed deep learning without sharing raw patient data." arXiv:1812.00564v1 [cs.LG] 3 Dec 2018.
Electronic Journal of Statistics, volume 12 No.1, Pages 960--984, The Institute of Mathematical Statistics and the Bernoulli Society, 2018
Applied and Computational Harmonic Analysis