Research
Publications
Preprints
- Priorconditioned Sparsity-Promoting Projection Methods for Deterministic and Bayesian Linear Inverse Problems. Jonathan Lindbloom, Mirjeta Pasha, Jan Glaubitz, and Youssef Marzouk (2025). arXiv
Journal publications
Efficient sparsity-promoting MAP estimation for Bayesian linear inverse problems. Jonathan Lindbloom, Jan Glaubitz, and Anne Gelb. Inverse Problems 41(2), 025001 (2025).
Complex-valued signal recovery using the Bayesian LASSO. Dylan Green, Jonathan Lindbloom, and Anne Gelb. SIAM/ASA Journal on Uncertainty Quantification 13(2), 831-861 (2025).
Empirical Bayesian inference for complex-valued signals using support-informed priors. Dylan Green, Jonathan Lindbloom, and Anne Gelb. AIMS Applied Mathematics for Modern Challenges 2(4) (2024).
Conference papers
- Complex-Valued Image Recovery from Multiple Measurements. Dylan Green, Jonathan Lindbloom, and Anne Gelb. 2024 IEEE Conference on Computational Imaging Using Synthetic Apertures (CISA) (2024).
Dissertation
- Advances in Computational Methods for Sparsity-Promoting Linear Inverse Problems. Jonathan Lindbloom. Ph.D. dissertation, Dartmouth College (2026).
Technical articles
Final Reports of the 2021 Los Alamos National Laboratory Computational Physics Student Summer Workshop. Angermeier et al. Los Alamos National Laboratory report (September 2021).
A Bayesian model of records. Jaime Sevilla and Jonathan Lindbloom. Authorea (May 2022).
Modelling a Time Series of Records with PyMC3. Jaime Sevilla and Jonathan Lindbloom. Authorea (September 2021).