Doctoral thesis: Holbrook A. Geometric Bayes, Diss.
UC Irvine, 2018. Advisor: Prof. Babak Shahbaba, Ph.D.
Preprints:
- Ko S, Suchard M, Holbrook A. Scaling Hawkes processes to one million COVID-19 cases, arXiv preprint, (2024): submitted to Statistics and Computing.
- Sheth A, Smith A, Holbrook A. Sparse Bayesian multidimensional scaling(s), arXiv preprint, (2024): submitted to JCGS.
- Lin C, Chen K, Lemey P, Suchard M, Holbrook A, Hsieh M. Quantum speedups for multiproposal MCMC, arXiv preprint, (2023): submitted to Bayesian Analysis.
- Li Y, Ghafari M, Holbrook A, Boonen I, Amor N, Catalano S, Webster J, et al. The evolutionary history of hepaciviruses, bioRxiv preprint, (2023): submitted to PNAS.
- Krometis J, Ringer H, Whitehead J, Glatt-Holtz N, Harris R, Holbrook A. Embracing uncertainty in "small data" problems: estimating earthquakes from historical anecdotes, arXiv preprint, (2022): working paper.
Book chapters:
- Holbrook A, Nishimura A, Ji X, Suchard M. "Computational statistics and data science in the twenty-first century." In Piegorsch,
W.W., Levine, R.A., Zhang, H.H., and Lee, T.C.M. (eds.). Computational
Statistics in Data Science, (2022):
John Wiley & Sons. DOI, PDF
Refereed publications:
- Didier G, Glatt-Holtz N, Holbrook A, Magee A, Suchard M. On the surprising effectiveness of a simple matrix exponential derivative approximation, with application to global SARS-CoV-2, Proceedings of the National Academy of Sciences, 121.3 (2024): e2318989121. PDF
- Su E, Weiss R, Nouri-Mahdavi K, Holbrook A. A spatially varying hierarchical random effects model for longitudinal macular structural data in glaucoma patients, arXiv preprint, (2024): To appear in Annals of Applied Statistics.
- Glatt-Holtz N, Holbrook A, Krometis J, Mondaini C. Parallel MCMC algorithms: theoretical foundations, algorithm design, case studies, Transactions of Mathematics and its Applications, 8.2 (2024).
- Magee A, Holbrook A, Pekar J, Caviedes-Solis I, Matsen F IV, Baele G, Wertheim J, Ji X, Lemey P, Suchard M. Random-effects substitution models for phylogenetics via scalable gradient approximations, Systematic Biology, 73.3 (2024): 562–578. PDF
- Tustison N, Yassa M, Rizvi B, Cook P, Holbrook A, Sathishkumar M, Tustison M, Gee J, Stone J, Avants B. ANTsX neuroimaging-derived structural phenotypes of UK Biobank, Scientific Reports, 14.8848 (2024). PDF
- Holbrook A. A quantum parallel Markov chain Monte Carlo, Journal of Computational and Graphical Statistics, 32.4 (2023): 1402-1415. PDF
- Zhang Z, Nishimura A, Trovão S, Cherry J, Holbrook A, Ji X, Lemey P, Suchard M. Accelerating Bayesian inference of dependency between mixed-type biological traits, PLOS Computational Biology, 19.8 (2023): e1011419. PDF
- Holbrook A. Generating MCMC proposals by randomly rotating the regular simplex, Journal of Multivariate Analysis, 194 (2023): 105106. PDF
- Hassler G, Gallone B, Aristide L, Allen W, Tolkoff M, Holbrook A, Baele G, Lemey P, Suchard M. Principled, practical, flexible, fast: a new approach to phylogenetic factor analysis, Methods in Ecology and Evolution, 13 (2022): 2181-2197. PDF
- Holbrook A, Ji X, Suchard M. From viral evolution to spatial contagion: a biologically modulated Hawkes model, Bioinformatics, 38.7 (2022): 1846-1856. PDF
- Holbrook A, Ji X, Suchard M. Bayesian mitigation of spatial coarsening for a Hawkes model applied to gunfire, wildfire and viral contagion, Annals of Applied Statistics, 16.1 (2022): 573-595. PDF
- Tustison N, Cook P, Holbrook A, et al. ANTsX: A dynamic ecosystem for quantitative biological and medical imaging, Scientific Reports, 11.9068 (2021). PDF
- Holbrook A, Loeffler C, Flaxman S, Suchard M. Scalable Bayesian inference for self-excitatory stochastic processes applied to big American gunfire data, Statistics and Computing, 31.4 (2021). PDF
- Holbrook A, Lemey P, Baele G, Dellicour S, Brockmann D, Rambaut A, Suchard M. Massive parallelization boosts big Bayesian multidimensional scaling, Journal of Computational and Graphical Statistics, 30.1 (2021): 11-24. PDF
- Holbrook A, Tustison N, Marquez F, Roberts J, Yassa M, Gillen D. Anterolateral entorhinal cortex thickness as a new biomarker for early detection of Alzheimer’s disease, Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring, 12.1 (2020). PDF
- Ji X, Zhang Z, Holbrook A, Nishimura A, Baele G, Rambaut A, Lemey P, Suchard M. Gradients do grow on trees: a linear-time O(N)-dimensional gradient for statistical phylogenetics, Molecular Biology and Evolution, 37.10 (2020): 3047–3060. PDF
- Shahbaba B, Lan S, Streets J, Holbrook A. Nonparametric Fisher geometry with application to density estimation, Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), in PMLR 124 (2020): 101-110. PDF
- Holbrook A, Lumley T, Gillen D. Estimating prediction error for complex samples, Canadian Journal of Statistics, 48.2 (2020): 204-221. PDF
- Lan S, Holbrook A, Elias G, Fortin N, Ombao H, Shahbaba B. Flexible Bayesian Dynamic Modeling of Correlation and Covariance Matrices, Bayesian Analysis, 15.4 (2020): 1199-1228. PDF
- Tustison N, Holbrook A, Avants B, Roberts J, Cook P, Reagh Z, Stone J, Gillen D, Yassa M. Longitudinal mapping of cortical thickness measurements: an Alzheimer’s Disease Neuroimaging Initiative-based evaluation study, Journal of Alzheimer's Disease, 71.1 (2019): 165-183. PDF
- Li L, Holbrook A, Shahbaba B, Baldi P.
Neural network gradient Hamiltonian Monte Carlo,
Computational Statistics,
34.1 (2019): 281-299. PDF
- Holbrook A.
Differentiating the pseudo determinant,
Linear Algebra and its Applications,
548 (2018): 293-304. PDF
- Holbrook A, Lan S, Vandenberg-Rodes A, Shahbaba B.
Geodesic Lagrangian Monte Carlo over the space of positive definite matrices: with application to Bayesian spectral density estimation,
Journal of Statistical Computation and Simulation,
88.5 (2018): 982-1002. PDF
- Holbrook A, Vandenberg-Rodes A, Fortin N, Shahbaba B.
A Bayesian supervised dual‐dimensionality reduction model for simultaneous decoding of LFP and spike train signals,
Stat,
6.1 (2017): 53-67. PDF
- Grill J, Holbrook A, Pierce A, Hoang D, Gillen D.
Attitudes toward potential participant registries,
Journal of Alzheimer's Disease,
56.3 (2017): 939-946. PDF