* indicates co-first authors
See full list of publications: Publications, Google Scholar
J. Yi*, A. M. Michalowska*, A. Shanbhag, R. J. Miller, J. Geers, W. Zhang, A. Killekar, N. Manral, M. Lemley,M. Buchwald, J. Kwiecinski, J. Zhou, P. Kavanagh, J. Liang, V. Builoff, T. Ruddy, A. Einstein, A. Feher, E. Miller, A. Sinusas, D. S Berman, D. Dey, P. Slomka. AI-based volumetric six-tissue body composition quanti cation from CT cardiac attenuation scans enhances mortality prediction: multicenter study. medRxiv (2024). Lancet Digital Health (to appear). pdf
J. Yi*, J. Gao*, T. Wang, X. Wu, W. Xu. Outlier detection using generative models with theoretical performance guarantees. IEEE transactions on information theory (to appear). pdf
R. Miller*, J. Yi*, A. Shanbhag, A. Michalowska, K. K. Patel, M. Lemley, G. Ramirez, J. Geers, P. Chareonthaitawee, S. Wopperer, D. S. Berman, M. Di Carli, D. Dey, P. J. Slomka. Deep learning-quantified body composition from positron emission tomography/computed tomography and cardiovascular outcomes: a multicentre study. European Heart Journal. 2025 Mar 30:ehaf131. pdf
J. Yi, S. Dasgupta, JF. Cai, M. Jacob, J. Gao, M. Cho, W. Xu. Separation-free super-resolution from compressed measurements is possible: an orthonormal atomic norm minimization approach. Information and Inference: A Journal of the IMA 12(3):2351-405, 2023. pdf
J. Yi, W. Xu. Necessary and sufficient null space condition for nuclear norm minimization in low-rank matrix recovery. IEEE Transactions on Information Theory 66(10): 6597-6604, 2020. pdf