KARTHIK BHARATH's Outputs (5)

RADIOHEAD: Radiogenomic analysis incorporating tumor heterogeneity in imaging through densities (2021)
Journal Article
Mohammed, S., Bharath, K., Kurtek, S., Rao, A., & Baladandayuthapani, V. (2021). RADIOHEAD: Radiogenomic analysis incorporating tumor heterogeneity in imaging through densities. Annals of Applied Statistics, 15(4), 1808-1830. https://doi.org/10.1214/21-AOAS1458

Recent technological advancements have enabled detailed investigation of associations between the molecular architecture and tumor heterogeneity through multisource integration of radiological imaging and genomic (radiogenomic) data. In this paper we... Read More about RADIOHEAD: Radiogenomic analysis incorporating tumor heterogeneity in imaging through densities.

Differential privacy over Riemannian manifolds (2021)
Presentation / Conference Contribution
Reimherr, M., Bharath, K., & Soto, C. (2021). Differential privacy over Riemannian manifolds.

In this work we consider the problem of releasing a differentially private statistical summary that resides on a Riemannian manifold. We present an extension of the Laplace or K-norm mechanism that utilizes intrinsic distances and volumes on the mani... Read More about Differential privacy over Riemannian manifolds.

Tangent functional canonical correlation analysis for densities and shapes, with applications to multimodal imaging data (2021)
Journal Article
Ho cho, M., Kurtek, S., & Bharath, K. (2022). Tangent functional canonical correlation analysis for densities and shapes, with applications to multimodal imaging data. Journal of Multivariate Analysis, 189, Article 104870. https://doi.org/10.1016/j.jmva.2021.104870

It is quite common for functional data arising from imaging data to assume values in infinite-dimensional manifolds. Uncovering associations between two or more such nonlinear functional data extracted from the same object across medical imaging moda... Read More about Tangent functional canonical correlation analysis for densities and shapes, with applications to multimodal imaging data.

Shape-Based Classification of Partially Observed Curves, With Applications to Anthropology (2021)
Journal Article
Matthews, G. J., Bharath, K., Kurtek, S., Brophy, J., Thiruvanthukal, G., & Harel, O. (2021). Shape-Based Classification of Partially Observed Curves, With Applications to Anthropology. Frontiers in Applied Mathematics and Statistics, 7, 1-14. https://doi.org/10.3389/fams.2021.759622

We consider the problem of classifying curves when they are observed only partially on their parameter domains. We propose computational methods for (i) completion of partially observed curves; (ii) assessment of completion variability through a nonp... Read More about Shape-Based Classification of Partially Observed Curves, With Applications to Anthropology.

Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse, and Fragmented Functional Data (2021)
Journal Article
Matuk, J., Bharath, K., Chkrebtii, O., & Kurtek, S. (2022). Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse, and Fragmented Functional Data. Journal of the American Statistical Association, 117(540), 1964-1980. https://doi.org/10.1080/01621459.2021.1893179

In many applications, smooth processes generate data that are recorded under a variety of observational regimes, including dense sampling and sparse or fragmented observations that are often contaminated with error. The statistical goal of registerin... Read More about Bayesian Framework for Simultaneous Registration and Estimation of Noisy, Sparse, and Fragmented Functional Data.