Papers

• Regression graphs and sparsity-inducing reparametrizations (with H. S. Battey and J. Rybak).
• Geometry-driven Bayesian inference for ultrametric covariance matrices (with T-H. Yao, Z. Wu, and V. Baladandayuthapani).
• Sampling and estimation on manifolds using the Langevin diffusion (with A. Lewis, A. Sharma and M. V. Tretyakov).
• Nonparametric regression for robot learning on manifolds (with P. C. Lopez-Custodio, A. Kucukyilmaz, S. P. Preston).
• Can tests for jumps be viewed as tests for clusters? (with V. Pozdnyakov and D. K. Dey).
• Unsharp measurements, joint measurability and classical distributions for some qudits (with H. S. Smitha Rao and S. Sirsi).

1. Probabilistic size-and-shape functional mixed models(with F. Wang, O. Chkrebtii and S. Kurtek).
   Neural Information Processing Systems (NeurIPS)(2024)


2. Topo-geometric analysis of variability in point clouds using Persistence Landscapes(with J. Matuk and S. Kurtek).
   IEEE Transactions on Pattern Analysis and Machine Intellingence (2024)


3. A diffusion approach to Stein's method on Riemannian manifolds(with H. Le, A. Lewis and C. Fallaize).
   Bernoulli(2024)


4. Tumor radiogenomics in Gliomas with Bayesian layered variable selection (with S. Mohammed, S. Kurtek, A. Rao and V. Baladandayuthapani).
   Medical Image Analysis(2023)


5. Spatially penalised registration of multivariate functional data (with X. Guo and S. Kurtek).
   Spatial Statisics(2023)


6. Shape and structure preserving differential privacy (with C. Soto, M. Reimherr and A. Slavkovic).
   Neural Information Processing Systems (NeurIPS)(2022)


7. Probabilistic learning of treatment trees in cancer (with T-H. Yao, Z. Wu, J. Li and V. Baladandayuthapani).
   Annals of Applied Statistics(2022)


8. Variograms for kriging and clustering of spatial functional data with phase variation (with X. Guo and S. Kurtek).
   Spatial Statistics (2022)


9. Differential privacy over Riemannian manifolds (with M. Reimherr and C. Soto).
   Neural Information Processing Systems (NeurIPS)(2021)


10. Tangent functional canonical correlation analysis for densities and shapes, with applications to multimodal imaging data (with M. H. Cho and S. Kurtek).
    Journal of Multivariate Analysis (2022)


11. Joint quasiprobability distribution on the measurement outcomes of MUB-driven operators (with H. S. Smitha Rao and S. Sirsi).
    Physics Letters A (2021)


12. Radiogenomic analysis incorporating tumor heterogeneity in imaging through densities (with S. Mohammed, S. Kurtek, A. Rao and V. Baladandayuthapani).
    Annals of Applied Statistics (2021)


13. Bayesian framework for simultaneous registration and estimation of noisy, sparse and fragmented functional data (with J. Matuk, S. Kurtek and O. Chkrebtii).
    Journal of the American Statistical Association (2021+)


14. Shape-based classification of partially observed curves, with applications to anthropology (with G. J. Matthews et al.).
    Frontiers in Applied Mathematics and Statistics (2021)


15. Geometric empirical Bayesian model for classification of functional data underdiverse sampling regimes (with J. Matuk, S. Kurtek and O. Chkrebtii).
    IEEE CVPR DiffCVML2021 (2021)


16. Discussion on 'On a class of objective priors from scoring rules' (with I. H. Jermyn).
    Bayesian Analysis (2020)


17. Measure of polymer performance based on correlated physical parameters (with S. Rudrappa et al.).
    Journal of Applied Polymer Science (2021)


18. Analysis of shape data: From landmarks to elastic curves (with S. Kurtek).
    WIREs Computational Statistics (2020)


19. Biomedical applications of geometric functional data analysis (with S. Kurtek, J. Matuk and S. Mohammed).
    In Handbook on variational methods for nonlinear geometric data (2020)


20. Distribution on warp maps for alignment of open and closed curves (with S. Kurtek).
    Journal of the American Statistical Association(2020) [talk]


21. Geometric variational approach to Bayesian inference (with A. Saha and S. Kurtek).
    Journal of the American Statistical Association (2020)


22. Invariance and identifiability issues for word embeddings (with R. Carrington and S. P. Preston).
    Neural Information Processing Systems (NeurIPS)(2019)[talk]


23. Mutually disjoint, maximally commuting set of physical observables for optimum state determination (with H. S. Smitha and S. Sirsi).
    Physica Scripta (2019)


24. Radiologic image-based statistical shape analysis of brain tumors (with S. Kurtek, A. Rao and V. Baladandayuthapani).
    Journal of the Royal Statistical Society (Series C) (2018) [talk]


25. Statistical tests for large tree-structured data (with P. Kambadur, D. K. Dey, A. Rao and V. Balandayuthapani).
    Journal of the American Statistical Association (2017) [talk]


26. Geometric approach to visualization of variability in functional data (with W. Xie, S. Kurtek and Y. Sun).
    Journal of the American Statistical Association (2017)[talk]


27. Multiaxial Representation of N-qubit Mixed Symmetric Separable States (with S. P Suma, S. Sirsi and S. Hegde).
    Physical Review A (2017)


28. Invited discussion on 'Sparse graphs using exchangeable random measures'.
    Journal of the Royal Statistical Society (Series B) (2017)


29. POVM construction: A simple recipe with applications to symmetric states (with S. Sirsi, S. P. Shilpashree and H. S. Smitha Rao).
    International Journal of Quantum Information (2017)


30. DEMARCATE: Density-based Magnetic Resonance Image Clustering for Assessing Tumor Heterogeneity in Cancer (with A. Saha et al.).
    NeuroImage (2016) [talk]


31. Functional data analysis techniques for the study of structural parameters in polymer composites (with S. Rudrappa et al.).
    Journal of Applied Crystallography (2016)


32. Bayesian sensitivity analysis with Fisher-Rao metric (with S. Kurtek).
    Biometrika (2015) [talk]


33. Spacings around an order statistic (with H. N. Nagaraja and F. Zhang).
    Annals of the Institute of Statistical Mathematics (2015).


34. On a clustering criterion for dependent observations.
    Journal of Statistical Planning and Inference (2014)


35. Asymptotics of a clustering criterion for smooth distributions (with V. Pozdnyakov and D. K. Dey).
    Electronic Journal of Statistics (2013)


36. Asymptotics of the Empirical Cross-over Function (with V. Pozdnyakov and D. K. Dey).
    Annals of the Institute of Statistical Mathematics (2013)


37. A note on density estimation for binary sequences.
    Statistics and Probability Letters (2013)


38. Test to distinguish a brownian motion from a brownian bridge using Polya process (with D. K. Dey).
    Statistics and Probability Letters (2011)