- Statistical and computational methodology in genetics, cancer biology, metagenomics, and morphometrics;
- Bayesian methodology for high-dimensional and complex data;
- Machine learning algorithms for the analysis of massive biological data;
- Integration of statistical inference with differential geometry and algebraic topology;
- Stochastic topology;
- Discrete Hodge theory;
- Inference in dynamical systems.
Youngsoo Baek et al.
Generalized Bayes approach to inverse problems with model misspecification
Michele Caprio et al.
Ergodic theorems in dynamic imprecise probability kinematics
Marzieh Eidi et al.
Irreducibility of Markov chains on simplicial complexes, the spectrum of the discrete Hodge Laplacian and homology
Nicolas Fraiman et al.
The shadow knows : empirical distributions of minimum spanning acycles and persistence diagrams of random complexes
Kimberly Roche et al.
Universal gut microbial relationships in the gut microbiome of wild baboons
Alyssa Shi et al.
Identifying risk factors for blindness from glaucoma at first presentation to a tertiary clinic
Yun Wei et al.
Minimum \(\Phi\)-distance estimators for finite mixing measures
Shreya Arya et al.
A sheaf-theoretic construction of shape space
Samuel I. Berchuck et al.
Bayesian non-parametric factor analysis for longitudinal spatial surfaces
Johannes R. Björk et al.
Synchrony and idiosyncrasy in the gut microbiome of wild baboons
Michele Caprio et al.
Concerning three classes of non-Diophantine arithmetics
Justin Curry et al.
How many directions determine a shape and other sufficiency results for two topological transforms