Genevera Allen
#105,602
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American statistician
Genevera Allen's AcademicInfluence.com Rankings
Genevera Allenmathematics Degrees
Mathematics
#8045
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#10927
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Statistics
#1107
World Rank
#1212
Historical Rank
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Mathematics
Genevera Allen's Degrees
- PhD Statistics Stanford University
- Masters Statistics Stanford University
- Bachelors Mathematics Stanford University
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Why Is Genevera Allen Influential?
(Suggest an Edit or Addition)According to Wikipedia, Genevera Irene Allen is an American statistician whose research has involved interpretable machine learning, the reproducibility of machine learning results, and the neuroscience of synesthesia. She is an associate professor of electrical and computer engineering, statistics, and computer science at Rice University, and also holds affiliations with Texas Children's Hospital and the Baylor College of Medicine.
Genevera Allen's Published Works
Number of citations in a given year to any of this author's works
Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author
Published Works
- Graphical models via univariate exponential family distributions (2013) (150)
- Graphical Models via Generalized Linear Models (2012) (137)
- TRANSPOSABLE REGULARIZED COVARIANCE MODELS WITH AN APPLICATION TO MISSING DATA IMPUTATION. (2009) (121)
- TCGA2STAT: simple TCGA data access for integrated statistical analysis in R (2016) (117)
- A Generalized Least-Square Matrix Decomposition (2014) (112)
- Sparse Higher-Order Principal Components Analysis (2012) (97)
- Mixed Graphical Models via Exponential Families (2014) (95)
- Convex biclustering (2014) (86)
- A Local Poisson Graphical Model for Inferring Networks From Sequencing Data (2013) (84)
- Molecular pathway identification using biological network-regularized logistic models (2013) (82)
- A review of multivariate distributions for count data derived from the Poisson distribution (2016) (81)
- Crowdsourced estimation of cognitive decline and resilience in Alzheimer's disease (2016) (78)
- Automatic Feature Selection via Weighted Kernels and Regularization (2013) (66)
- On Poisson Graphical Models (2013) (65)
- Tensor network factorizations: Relationships between brain structural connectomes and traits (2018) (60)
- A Log-Linear Graphical Model for inferring genetic networks from high-throughput sequencing data (2012) (60)
- Sparse non-negative generalized PCA with applications to metabolomics (2011) (54)
- Imaging genetics via sparse canonical correlation analysis (2013) (48)
- Inference with transposable data: modelling the effects of row and column correlations (2010) (47)
- Regularized partial least squares with an application to NMR spectroscopy (2012) (44)
- Neural Networks of Colored Sequence Synesthesia (2013) (33)
- Within Group Variable Selection through the Exclusive Lasso (2015) (29)
- Two Sample Inference for Populations of Graphical Models with Applications to Functional Connectivity (2015) (29)
- On the Reproducibility of TCGA Ovarian Cancer MicroRNA Profiles (2013) (28)
- Resting state functional MRI reveals abnormal network connectivity in neurofibromatosis 1 (2015) (28)
- A Generalized Least Squares Matrix Decomposition (2011) (28)
- Dynamic Visualization and Fast Computation for Convex Clustering via Algorithmic Regularization (2019) (23)
- Multi-way functional principal components analysis (2013) (22)
- Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity (2016) (20)
- Regularized Tensor Factorizations and Higher-Order Principal Components Analysis (2012) (20)
- XMRF: an R package to fit Markov Networks to high-throughput genetics data (2015) (19)
- A General Framework for Mixed Graphical Models (2014) (18)
- Graphical Models and Dynamic Latent Factors for Modeling Functional Brain Connectivity (2019) (17)
- Sparse and Functional Principal Components Analysis (2013) (17)
- Integrative Generalized Convex Clustering Optimization and Feature Selection for Mixed Multi-View Data (2019) (15)
- Integrated Principal Components Analysis (2018) (15)
- Quantifying cognitive resilience in Alzheimer’s Disease: The Alzheimer’s Disease Cognitive Resilience Score (2020) (15)
- ADMM Algorithmic Regularization Paths for Sparse Statistical Machine Learning (2015) (15)
- Graph quilting: graphical model selection from partially observed covariances. (2019) (13)
- Downregulation of glial genes involved in synaptic function mitigates Huntington's disease pathogenesis (2021) (13)
- Relationships between Human Brain Structural Connectomes and Traits (2018) (13)
- Local‐aggregate modeling for big data via distributed optimization: Applications to neuroimaging (2014) (11)
- Detecting hidden batch factors through data-adaptive adjustment for biological effects (2018) (11)
- Feature selection for data integration with mixed multiview data (2019) (11)
- Conditional Random Fields via Univariate Exponential Families (2013) (10)
- Data and text mining TCGA 2 STAT : simple TCGA data access for integrated statistical analysis in R (2016) (10)
- MP-Boost: Minipatch Boosting via Adaptive Feature and Observation Sampling (2020) (8)
- Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity (2016) (8)
- Randomized Approach to Differential Inference in Multi-subject Functional Connectivity (2013) (8)
- HepatoScore‐14: Measures of Biological Heterogeneity Significantly Improve Prediction of Hepatocellular Carcinoma Risk (2020) (7)
- Identifying cancer biomarkers through a network regularized Cox model (2013) (7)
- Minipatch Learning as Implicit Ridge-Like Regularization (2021) (6)
- Feature Selection for Huge Data via Minipatch Learning (2020) (6)
- Experiential Learning in Data Science: Developing an Interdisciplinary, Client-Sponsored Capstone Program (2021) (5)
- Statistical data integration: Challenges and opportunities (2017) (5)
- Thresholded Graphical Lasso Adjusts for Latent Variables: Application to Functional Neural Connectivity (2021) (5)
- The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: summary and innovation in genomics (2017) (5)
- Mixed Effects Models to Find Differences in Multi-Subject Functional Connectivity (2015) (4)
- Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates (2020) (4)
- A CRISPR toolbox for generating intersectional genetic mouse models for functional, molecular, and anatomical circuit mapping (2022) (4)
- Genomic region detection via Spatial Convex Clustering (2016) (3)
- Network Clustering for Latent State and Changepoint Detection (2021) (3)
- Sparse regression for extreme values (2020) (3)
- Correlation imputation in single cell RNA-seq using auxiliary information and ensemble learning (2020) (3)
- Machine Learning: The View from Statistics (2019) (3)
- Thresholded Graphical Lasso Adjusts for Latent Variables (2022) (2)
- To the Fairness Frontier and Beyond: Identifying, Quantifying, and Optimizing the Fairness-Accuracy Pareto Frontier (2022) (2)
- Statistical Research and Training Under the Brain Initiative (2014) (2)
- Comment on article by Hoff (2011) (2)
- Singular Value Decomposition and High Dimensional Data (2013) (2)
- An Automated Respiratory Data Pipeline for Waveform Characteristic Analysis (2021) (2)
- Population Inference for Node Level Differences in Multi-subject Functional Connectivity (2015) (2)
- Supervised convex clustering. (2020) (2)
- A Low-Rank Tensor Completion Approach for Imputing Functional Neuronal Data from Multiple Recordings (2022) (1)
- Handbook of Graphical Models (2020) (1)
- Inference for Interpretable Machine Learning: Fast, Model-Agnostic Confidence Intervals for Feature Importance (2022) (1)
- Learning Gaussian Graphical Models with Differing Pairwise Sample Sizes (2022) (1)
- Correlation Imputation for Single-Cell RNA-seq (2022) (1)
- Dynamic Visualization and Fast Computation for Convex Clustering and Bi-Clustering (2019) (1)
- Molecular pathway identification using biological network-regularized logistic models (2013) (1)
- Fast and interpretable consensus clustering via minipatch learning (2021) (1)
- Spatio-Temporal Dimension Reduction via Sparse Generalized PCA (2011) (1)
- Functional screening of lysosomal storage disorder genes identifies modifiers of alpha-synuclein mediated neurodegeneration (2022) (1)
- Clustered Gaussian Graphical Model Via Symmetric Convex Clustering (2019) (1)
- The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: from big data to big analytical tools (2017) (1)
- Low-Rank Covariance Completion for Graph Quilting with Applications to Functional Connectivity (2022) (1)
- Simultaneous Grouping and Denoising via Sparse Convex Wavelet Clustering (2020) (1)
- Graphical Model Inference with Erosely Measured Data (2022) (1)
- Population Inference for Node Level Differences in Functional Connectivity (2015) (1)
- Interpretable Visualization and Higher-Order Dimension Reduction for ECoG Data (2020) (1)
- SPA-STOCSY: An Automated Tool for Identification of Annotated and Non-Annotated Metabolites in High-Throughput NMR Spectra (2023) (0)
- The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: from big data to big analytical tools (2017) (0)
- Sparse Generalized Principal Components Analysis with Applications to Neuroimaging (2013) (0)
- KNIFE: Kernel Iterative Feature Extraction (2009) (0)
- The International Conference on Intelligent Biology and Medicine (ICIBM) 2016: summary and innovation in genomics (2017) (0)
- Experiential Learning in Data Science Through a Novel Client-Facing Consulting Course (2022) (0)
- Modulating glial genes involved in synaptic function mitigates pathogenesis and behavioral deficits in a Drosophila model of Huntington’s Disease (2020) (0)
- Model-Agnostic Confidence Intervals for Feature Importance: A Fast and Powerful Approach Using Minipatch Ensembles (2022) (0)
- Detection of Junctional Ectopic Tachycardia by Central Venous Pressure (2021) (0)
- Subbotin Graphical Models for Extreme Value Dependencies with Applications to Functional Neuronal Connectivity (2021) (0)
- VIA SPARSE CANONICAL CORRELATION ANALYSIS (2013) (0)
- Local-Aggregate Modeling for Multi-subject Neuroimage Data via Distributed Optimization (2013) (0)
- Fast and Accurate Graph Learning for Huge Data via Minipatch Ensembles (2021) (0)
- Generalizing Principal Components Analysis (2011) (0)
- An automated respiratory data pipeline for waveform characteristic analysis (2022) (0)
- Supplement to “ A Generalized Least Squares Matrix Decomposition ” (2013) (0)
- Gaussian Graphical Model Selection for Huge Data via Minipatch Learning (2021) (0)
- Comments on “visualizing statistical models”: Visualizing modern statistical methods for Big Data (2015) (0)
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What Schools Are Affiliated With Genevera Allen?
Genevera Allen is affiliated with the following schools:
