Ranjan Maitra
YOU?
Author Swipe
View article: Computational Improvements to the Kernel k$$ k $$‐Means Clustering Algorithm
Computational Improvements to the Kernel k$$ k $$‐Means Clustering Algorithm Open
Kernel k‐means ( k k ‐means) extends the standard k‐means clustering method to identify generally shaped clusters by employing the k ‐means algorithm in a higher‐dimensional space. Current implementations of k k ‐means are rather naive. We…
View article: Latent characterization of the complete BATSE gamma-ray bursts catalogue using Gaussian mixture of factor analysers and model-estimated overlap-based syncytial clustering
Latent characterization of the complete BATSE gamma-ray bursts catalogue using Gaussian mixture of factor analysers and model-estimated overlap-based syncytial clustering Open
Characterizing and distinguishing gamma-ray bursts (GRBs) has interested astronomers for many decades. While some authors have found two or three groups of GRBs by analysing only a few parameters, recent work identified five ellipsoidally …
View article: Elliptically Contoured Tensor-variate Distributions with Application to Image Learning
Elliptically Contoured Tensor-variate Distributions with Application to Image Learning Open
Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate for data arising from distributions with heavier or lighter tails. We study a general family of elliptically co…
View article: A Machine Learning Approach to Improve the Usability of Severe Thunderstorm Wind Reports
A Machine Learning Approach to Improve the Usability of Severe Thunderstorm Wind Reports Open
Many concerns are known to exist with thunderstorm wind reports in the National Center for Environmental Information Storm Events Database , including the overestimation of wind speed, changes in report frequency due to population density,…
View article: Fast Matrix-Free Methods for Model-Based Personalized Synthetic MR Imaging
Fast Matrix-Free Methods for Model-Based Personalized Synthetic MR Imaging Open
Synthetic Magnetic Resonance (MR) imaging predicts images at new design parameter settings from a few observed MR scans. Model-based methods, that use both the physical and statistical properties underlying the MR signal and its acquisitio…
View article: A practical model‐based segmentation approach for improved activation detection in single‐subject functional magnetic resonance imaging studies
A practical model‐based segmentation approach for improved activation detection in single‐subject functional magnetic resonance imaging studies Open
Functional magnetic resonance imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low‐signal contexts and single‐subject studies. Accurate activation detection can …
View article: The envelope of a complex Gaussian random variable
The envelope of a complex Gaussian random variable Open
The envelope of an elliptical Gaussian complex vector, or equivalently, the amplitude or norm of a bivariate normal random vector has application in many weather and signal processing contexts. We explicitly characterize its distribution i…
View article: A machine learning approach to mitigate problems with estimated winds in severe thunderstorm wind damage reports
A machine learning approach to mitigate problems with estimated winds in severe thunderstorm wind damage reports Open
<p>In the United States, the official database of severe thunderstorm wind reports arguably has more serious deficiencies than those of tornadoes and hail. Roughly 90% of the thunderstorm wind reports in the Storm Events database dur…
View article: Fast matrix-free methods for model-based personalized synthetic MR imaging
Fast matrix-free methods for model-based personalized synthetic MR imaging Open
Synthetic Magnetic Resonance (MR) imaging predicts images at new design parameter settings from a few observed MR scans. Model-based methods, that use both the physical and statistical properties underlying the MR signal and its acquisitio…
View article: Personalized synthetic MR imaging with deep learning enhancements
Personalized synthetic MR imaging with deep learning enhancements Open
Purpose Personalized synthetic MRI (syn‐MRI) uses MR images of an individual subject acquired at a few design parameters (echo time, repetition time, flip angle) to obtain underlying parametric maps, from where MR images of that individual…
View article: Elliptically-Contoured Tensor-variate Distributions with Application to Improved Image Learning
Elliptically-Contoured Tensor-variate Distributions with Application to Improved Image Learning Open
Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate when data comes from distributions with heavier or lighter tails. We study a general family of elliptically con…
View article: Reduced-Rank Tensor-on-Tensor Regression and Tensor-Variate Analysis of Variance
Reduced-Rank Tensor-on-Tensor Regression and Tensor-Variate Analysis of Variance Open
Fitting regression models with many multivariate responses and covariates can be challenging, but such responses and covariates sometimes have tensor-variate structure. We extend the classical multivariate regression model to exploit such …
View article: Quantitative matching of forensic evidence fragments utilizing <scp>3D</scp> microscopy analysis of fracture surface replicas
Quantitative matching of forensic evidence fragments utilizing <span>3D</span> microscopy analysis of fracture surface replicas Open
Silicone casts are widely used by practitioners in the comparative analysis of forensic items. Fractured surfaces carry unique details that can provide accurate quantitative comparisons of forensic fragments. In this study, a statistical a…
View article: Fully Three-Dimensional Radial Visualization
Fully Three-Dimensional Radial Visualization Open
We develop methodology for three-dimensional (3D) radial visualization (RadViz) of multidimensional datasets. The classical two-dimensional (2D) RadViz visualizes multivariate data in the 2D plane by mapping every observation to a point in…
View article: Fully Three-dimensional Radial Visualization
Fully Three-dimensional Radial Visualization Open
We develop methodology for three-dimensional (3D) radial visualization (RadViz) of multidimensional datasets. The classical two-dimensional (2D) RadViz visualizes multivariate data in the 2D plane by mapping every observation to a point in…
View article: Fully Three-Dimensional Radial Visualization
Fully Three-Dimensional Radial Visualization Open
We develop methodology for three-dimensional (3D) radial visualization (RadViz) of multidimensional datasets. The classical two-dimensional (2D) RadViz visualizes multivariate data in the 2D plane by mapping every observation to a point in…
View article: Multi-layered characterisation of hot stellar systems with confidence
Multi-layered characterisation of hot stellar systems with confidence Open
Understanding the physical and evolutionary properties of Hot Stellar Systems (HSS) is a major challenge in astronomy. We studied the dataset on 13 456 HSS of Misgeld & Hilker (2011, MNRAS, 414, 3 699) that includes 12 763 candidate globul…
View article: Exploratory Factor Analysis of Data on a Sphere
Exploratory Factor Analysis of Data on a Sphere Open
Data on high-dimensional spheres arise frequently in many disciplines either naturally or as a consequence of preliminary processing and can have intricate dependence structure that needs to be understood. We develop exploratory factor ana…
View article: Fracture Mechanics-Based Quantitative Matching of Forensic Evidence Fragments
Fracture Mechanics-Based Quantitative Matching of Forensic Evidence Fragments Open
Fractured metal fragments with rough and irregular surfaces are often found at crime scenes. Current forensic practice visually inspects the complex jagged trajectory of fractured surfaces to recognize a ``match'' using comparative microsc…
View article: Model-based clustering of partial records.
Model-based clustering of partial records. Open
Partially recorded data are frequently encountered in many applications and usually clustered by first removing incomplete cases or features with missing values, or by imputing missing values, followed by application of a clustering algori…
View article: Model-based Personalized Synthetic MR Imaging
Model-based Personalized Synthetic MR Imaging Open
Synthetic Magnetic Resonance (MR) imaging predicts images at new design parameter settings from a few observed MR scans. Model-based methods, that use both the physical and statistical properties underlying the MR signal and its acquisitio…
View article: Fast matrix-free methods for model-based personalized synthetic MR imaging
Fast matrix-free methods for model-based personalized synthetic MR imaging Open
Synthetic Magnetic Resonance (MR) imaging predicts images at new design parameter settings from a few observed MR scans. Model-based methods, that use both the physical and statistical properties underlying the MR signal and its acquisitio…
View article: A Practical Model-based Segmentation Approach for Accurate Activation Detection in Single-Subject functional Magnetic Resonance Imaging Studies
A Practical Model-based Segmentation Approach for Accurate Activation Detection in Single-Subject functional Magnetic Resonance Imaging Studies Open
Functional Magnetic Resonance Imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low-signal contexts and single-subject studies. Accurate activation detection can …
View article: A practical model-based segmentation approach for improved activation detection in single-subject functional Magnetic Resonance Imaging studies
A practical model-based segmentation approach for improved activation detection in single-subject functional Magnetic Resonance Imaging studies Open
Functional Magnetic Resonance Imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low-signal contexts and single-subject studies. Accurate activation detection can …
View article: Classification With the Matrix-Variate-<i>t</i> Distribution
Classification With the Matrix-Variate-<i>t</i> Distribution Open
Matrix-variate distributions can intuitively model the dependence structure of matrix-valued observations that arise in applications with multivariate time series, spatio-temporal, or repeated measures. This article develops an expectation…
View article: A Matrix-Free Likelihood Method for Exploratory Factor Analysis of High-Dimensional Gaussian Data
A Matrix-Free Likelihood Method for Exploratory Factor Analysis of High-Dimensional Gaussian Data Open
This technical note proposes a novel profile likelihood method for estimating the covariance parameters in exploratory factor analysis of high-dimensional Gaussian datasets with fewer observations than number of variables. An implicitly re…
View article: Reduced-Rank Tensor-on-Tensor Regression and Tensor-variate Analysis of Variance
Reduced-Rank Tensor-on-Tensor Regression and Tensor-variate Analysis of Variance Open
Fitting regression models with many multivariate responses and covariates can be challenging, but such responses and covariates sometimes have tensor-variate structure. We extend the classical multivariate regression model to exploit such …