Recent Publications

Year 2020 Publications
  1. 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.
  2. 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.
  3. 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.
  4. 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
  1. M. Dai, Z. Zhang, and A. Srivastava, Discovering Common Change-Point Patterns in  Functional Connectivity Across Subjects, Medical Image Analysis, volume 58, December 2019.
  2. 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.
  3. S. Dasgupta, D. Pati, and A. Srivastava, A Two-Step Geometric Framework for Density Estimation, accepted, Statistica Sinica, 2018.
  4. 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.
  5. 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.
  6. 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.  
  7. 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
  1. 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.
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
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