publications

Papers

1. Lila, E., Zhang, W., and Rane, S. Interpretable discriminant analysis for functional data supported on random non-linear domains arXiv, 2021 [arXiv]
2. Jiang, C-R, Lila, E., Aston, J.A.D., and Wang, J-L Eigen-Adjusted Functional Principal Component Analysis Journal of Computational and Graphical Statistics, accepted, 2022 [arXiv]
3. Lila, E., and Aston, J.A.D. Functional random effects modeling of brain shape and connectivity Annals of Applied Statistics, to appear, 2021 [arXiv]
4. Lila, E., Arridge, S., and Aston, J.A.D. Representation and reconstruction of covariance operators in linear inverse problems Inverse Problems, 2020 [PDF] [arXiv]
5. Lila, E., and Aston, J.A.D. Statistical Analysis of Functions on Surfaces, With an Application to Medical Imaging Journal of the American Statistical Association, 2020 [PDF] [arXiv]
6. Lila, E., Aston, J.A.D., and Sangalli, L.M. Smooth Principal Component Analysis over two-dimensional manifolds with an application to Neuroimaging Annals of Applied Statistics, 2016 [PDF] [arXiv]

Book Chapters

1. Lila, E., Aston, J.A.D., and Sangalli, L.M. Functional data analysis of neuroimaging signals associated with cerebral activity in the brain cortex Functional Statistics and Related Fields, Springer Ser. Contribution to Statistics, 2017 [PDF]