Year 2020 Publications
- K. Ahn, J. D. Tucker, W. Wu, and A. Srivastava, Regression Models using Shapes of Functions as Predictors, Computational and Statistical Data Analysis, volume 151, November 2020.
- G. Wang, H. Laga, J. Jia, S. Miklavcic, A. Srivastava, Statistical Analysis and Modeling of Geometry and Topology of Plant Roots, Journal of Theoretical Biology, volume 486, February 2020.
- B. Ben Amor, A. Srivastava, P. Turaga, and G. Coleman, A Framework for Interpretable Full-Body Kinematic Description Using Geometric and Functional Analysis, IEEE Journal of Biomedical and Health Informatics, volume 67, issue 6, pages 1761-1774, June 2020. DOI: 10.1109/TBME.2019.2946682.
- M. Dai, Z. Zhang, and A. Srivastava, Analyzing Dynamical Brain Functional Connectivity as Trajectories on Space of Covariance Matrices, IEEE Transactions on Medical Image Analysis, volume 39, issue 3, pages 611-620, March 2020.
Year 2019 Publications
- M. Dai, Z. Zhang, and A. Srivastava, Discovering Common Change-Point Patterns in Functional Connectivity Across Subjects, Medical Image Analysis, volume 58, December 2019.
- M. Rosenthal, D. Bryner, F. Huffer, S. Evans, A. Srivastava, and N. Neretti, Bayesian Estimation of 3D Chromosomal Structure from Single Cell Hi-C Data, Journal of Computational Biology, volume 26, issue 11, pages 1191-1202, November 2019.
- S. Dasgupta, D. Pati, and A. Srivastava, A Two-Step Geometric Framework for Density Estimation, accepted, Statistica Sinica, 2018.
- Z. Zhang, E. Klassen, and A. Srivastava, Robust Kernel Density Estimation and Two-Sample Hypothesis Test in Euclidean and Spherical Domains, volume 81, number 1, pages 144-171, Sankhya, February 2019.
- S. Dasgupta, D. Pati, and A. Srivastava, Bayesian Shape-Constrained Density Estimation, Quarterly of Applied Mathematics, volume LXVII, number 2, pages 399-422, June 2019.
- M. Dai and A. Srivastava, Efficient Video-Based Action Recognition Using Dimension Reduction of Covariance Trajectories, CVPR — 3rd International Workshop on Compact and Efficient Feature Representation and Learning (CEFRL) in Computer Vision, 2019.
- S. Dasgupta, J. Cordova, R. Argandeh, and A. Srivastava, Clustering household electrical load profiles using elastic shape analysis, IEEE PowerTech, Milano, Italy, June 2019.
Year 2018 Publications
- A. Duncan, E. Klassen, and A. Srivastava, Statistical Shape Analysis of Simplified Neuronal Trees, Annals of Applied Statistics, volume 12, number 3, pages 1385-1421, 2018.
- Z. Zhang. J. Su, E. Klassen, H. Le, and A. Srivastava, Rate-Invariant Analysis of Covariance Trajectories, Journal of Mathematical Imaging and Vision, volume 60, issue 8, pages 1306-1323, October 2018.
- J. Cordova, C. Soto, M. Gilanifar, Y. Zhou, A. Srivastava, and R. Arghandeh, Shape-Preserving Incremental Learning for Power Systems Fault Detection, IEEE Control Letters, volume 3, issue 1, pages 85-90, July 2018.
- Z. Zhang, E. Klassen and A. Srivastava, Phase-Amplitude Separation and Modeling of Spherical Trajectories, Journal of Computational and Graphical Statistics, volume 27, issue 1, pages 85-97, January 2018.
- Z. Zhang, M. Descoteaux, J. Zhang, G. Girard, M. Chamberland. D. Dunson, A. Srivastava, H. Zhu, Mapping Population-Based Structural Connectomes, Neuroimage, volume 172, pages 130-145, May 2018.
- S. Dasgupta, D. Pati, and A. Srivastava, Shape-Constrained and Unconstrained Density Estimation Using Geometric Exploration, IEEE Conference on Statistical Signal Processing, Freiburg, Germany, June 2018.