Publications
Battiston, M., Cappello, L., (2026) “Bayesian Predictive Inference Beyond Martingales”, Journal of Machine Learning Research, to appear [arXiv][code to reproduce]
Cappello, L., Walker, S. G., (2026) “Recursive Nonparametric Predictive for a Discrete Regression Model.” Computational Statistics and Data Analysis, 215 (SBSS Best Student Paper Prize at JSM 2018, BNP at Paris 2017 Best Poster Award) [journal]
Cappello, L., Lo, W.T.J., Zhang, J.Z., Xu, P., Barrow, D., Chopra, I., Clark, A. G., Wells, M. T., Kim, J. (2025) “Bayesian phylodynamic inference of population dynamics with dormancy”. Proceedings of the National Academy of Sciences (PNAS) to appear [bioRxiv] [journal] [software]
Cappello, L., Padilla, O. M., (2025) ``Bayesian variance change point detection withcredible sets.” IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear [arXiv] [software]
Cappello, L., Veber, A., Palacios, J. A., (2024) “An Efficient Coalescent Model for Heterochronously Sampled Molecular Data.” Journal of the American Statistical Association, 119 (548), 2437-2449 [journal] [arXiv] [software]
Cappello, L., Padilla, O. M., Palacios, J. A., (2023) “Bayesian Change Point Detection with Spike and Slab Priors.” Journal of Computational and Graphical Statistics, in press [journal] [arXiv] [software]
Cappello, L.*, Kim, J.* , Palacios, J. A., (2023) “Bayesian Inference of Dependent Population Dynamics in Coalescent Models.” PLOS Computational Biology, in press [biorXiv] [software]. * first authors
Parikh, V. N. , Ioannidis, A. G. , …, Cappello, L., … Ashley, E. A. , (2022) “Deconvoluting complex correlates of COVID19 severity with a multi-omic pandemic tracking strategy.” Nature Communications, 13, 5107 [journal] [medrXiv]
Cappello, L., Kim, J. , Liu, S. , Palacios, J. A., (2022) “Statistical Challenges in Tracking the Evolution of SARS-CoV-2.” Statistical Science, 37(2): 162-182 [journal]
Cappello, L., Palacios, J. A., (2021) “Adaptive Preferential Sampling in Phylodynamics.” Journal of Computational and Graphical Statistics, in press, [arXiv] [journal][software]
Cappello, L., Ghosh, S., Palacios, J. A., (2020) Discussion (Invited) on “Horseshoe-based Bayesian Nonparametric Estimation of Effective Population Size Trajectories.” Biometrics, 76 (3) 691-694 [journal]
Cappello, L., Palacios, J. A., (2020) “Sequential Importance Sampling Algorithms for Multi-Resolution Kingman-Tajima Coalescent Counting.” Annals of Applied Statistics, 14 (2) 727-751. [arXiv] [journal][software]
Palacios, J. A., Veber, A. , Cappello, L., Wang, Z., Wakeley, J., Ramachandran, S., (2019) “Bayesian Estimation of Population Size Changes by Sampling Tajima’s Tree.” Genetics, 213 (3) 967-986 [bioRxiv] [journal][software]
Cappello, L., Walker, S. G., (2018) “A Recursive Multivariate Inversion of a Laplace Transform for Probability Distributions.”, Methodology and Computing in Applied Probability, 20 777-797. [journal]
Submitted Papers
Cappello, L., Walker, S. G., “Recursive Estimation of Probability Distributions.”
Bianco, N., Cappello, L., “Computationally efficient segmentation for non-stationary time series with oscillatory patterns”, [software]
Berlind, D., Cappello, L., Padilla, O. M., “A Bayesian framework for change-point detection with uncertainty quantification”, [arXiv][software]
Papers in Preparation
Cappello, L., Walker, S. G., “Bivariate Bayesian Recursive Predictive Distributions.”
Cappello, L., Walker, S. G., “Recursive Sampling from a Distribution given its Laplace Transform.”