A. Schwartzman

发表

Cross‐subject comparison of principal diffusion direction maps

R. Dougherty, Jonathan E. Taylor, A. Schwartzman, 2005, Magnetic resonance in medicine.

False discovery control in large‐scale spatial multiple testing

Wenguang Sun, T. Cai, B. Reich, 2015, Journal of the Royal Statistical Society. Series B, Statistical methodology.

The effect of correlation in false discovery rate estimation.

Xihong Lin, A. Schwartzman, 2011, Biometrika.

FALSE DISCOVERY RATE ANALYSIS OF BRAIN DIFFUSION DIRECTION MAPS.

R. Dougherty, Jonathan E. Taylor, A. Schwartzman, 2008, The annals of applied statistics.

Characterizing brain tissue by assessment of the distribution of anisotropic microstructural environments in diffusion‐compartment imaging (DIAMOND)

A. Schwartzman, S. Warfield, B. Scherrer, 2016, Magnetic resonance in medicine.

Paradoxical Results in Multidimensional Item Response Theory

G. Hooker, A. Schwartzman, M. Finkelman, 2009 .

Multiple testing of local extrema for detection of change points

A. Schwartzman, Dan Cheng, Zhibing He, 2015, Electronic Journal of Statistics.

MULTIPLE TESTING OF LOCAL MAXIMA FOR DETECTION OF PEAKS IN 1D.

Armin Schwartzman, Robert J Adler, R. Adler, 2011, Annals of statistics.

Inference for eigenvalues and eigenvectors of Gaussian symmetric matrices

Jonathan E. Taylor, A. Schwartzman, W. Mascarenhas, 2008, 0901.3290.

Group Comparison of Eigenvalues and Eigenvectors of Diffusion Tensors

R. Dougherty, Jonathan E. Taylor, A. Schwartzman, 2010, Journal of the American Statistical Association.

Convolutional neural network-automated hepatobiliary phase adequacy evaluation may optimize examination time.

Alexandra N. Schlein, Ryan L Brunsing, A. Schwartzman, 2020, European journal of radiology.

Standardization of multivariate Gaussian mixture models and background adjustment of PET images in brain oncology

M. Li, A. Schwartzman, 2017, The Annals of Applied Statistics.

Complex data analysis in high‐resolution SSFP fMRI

Morteza Shahram, John M Pauly, Armin Schwartzman, 2007, Magnetic resonance in medicine.

Lognormal Distributions and Geometric Averages of Symmetric Positive Definite Matrices

Armin Schwartzman, A. Schwartzman, 2016, International statistical review = Revue internationale de statistique.

Peak Detection as Multiple Testing

R. Adler, A. Schwartzman, Yulia Gavrilov, 2010, 1008.1924.

Observing the Ice‐Covered Weddell Gyre With Profiling Floats: Position Uncertainties and Correlation Statistics

S. Riser, L. Talley, A. Schwartzman, 2018, Journal of Geophysical Research: Oceans.

2 0 D ec 2 01 7 Uniqueness questions in a scaling-rotation geometry on the space of symmetric positive-definite matrices

A. Schwartzman, D. Groisser, Sungkyu Jung, 2019 .

Uniqueness questions in a scaling-rotation geometry on the space of symmetric positive-definite matrices

A. Schwartzman, D. Groisser, Sungkyu Jung, 2017, 1702.03237.

Empirical null and false discovery rate inference for exponential families

Armin Schwartzman, A. Schwartzman, 2008, 0901.4007.

Expected Number and Height Distribution of Critical Points of Smooth Isotropic Gaussian Random Fields.

A. Schwartzman, Dan Cheng, 2015, Bernoulli : official journal of the Bernoulli Society for Mathematical Statistics and Probability.

SAGE-Seq Gene expression profiling of human breast tissue samples using Material

Clifford A. Meyer, Jun S. Liu, X. Liu, 2010 .

Gene expression profiling of human breast tissue samples using SAGE-Seq.

Clifford A. Meyer, Jun S. Liu, Armin Schwartzman, 2010, Genome research.

MULTIPLE TESTING OF LOCAL MAXIMA FOR DETECTION OF PEAKS IN CHIP-SEQ DATA.

Clifford A. Meyer, A. Schwartzman, A. Jaffe, 2013, The annals of applied statistics.

Simultaneous confidence bands for functional data using the Gaussian Kinematic formula.

A. Schwartzman, F. Telschow, 2019, Journal of statistical planning and inference.

Submitted to the Annals of Statistics ESTIMATION OF EXPECTED EULER CHARACTERISTIC CURVES OF NONSTATIONARY SMOOTH GAUSSIAN RANDOM FIELDS By

A. Schwartzman, Dan Cheng, F. Telschow, 2019 .

A simple, consistent estimator of SNP heritability from genome-wide association studies

Rong W. Zablocki, W. Thompson, A. Schork, 2019 .

Comment on "Correlated z-values and the accuracy of large-scale statistical estimates" by Bradley Efron.

A. Schwartzman, 2010, Journal of the American Statistical Association.

Multiple testing of local maxima for detection of peaks on the (celestial) sphere

Y. Fantaye, A. Schwartzman, Dan Cheng, 2016, Bernoulli.

Geometric foundations for scaling-rotation statistics on symmetric positive definite matrices: Minimal smooth scaling-rotation curves in low dimensions

A. Schwartzman, D. Groisser, Sungkyu Jung, 2016, 1602.01187.

Assessing NARCCAP climate model effects using spatial confidence regions.

A. Schwartzman, S. McGinnis, J. French, 2017, Advances in statistical climatology, meteorology and oceanography.

Detection of local DNA copy number changes in lung cancer population analyses using a multi-scale approach

Xihong Lin, A. Schwartzman, D. Christiani, 2015, Communications in statistics. Case studies, data analysis and applications.

Comment on "Correlated z-values and the accuracy of large-scale statistical estimates" by Bradley Efron.

A. Schwartzman, 2010, Journal of the American Statistical Association.

Functional delta residuals and applications to functional effect sizes

A. Schwartzman, F. Telschow, Samuel Davenport, 2020 .

Confidence regions for excursion sets in asymptotically Gaussian random fields, with an application to climate

Max Sommerfeld, A. Schwartzman, S. Sain, 2015, 1501.07000.

Lognormal Distributions and Geometric Averages of Positive Definite Matrices

A. Schwartzman, 2014, 1407.6383.

Unexpected topology of the temperature fluctuations in the cosmic microwave background

H. Edelsbrunner, R. Adler, H. Wagner, 2018, Astronomy & Astrophysics.

Confidence Regions for Spatial Excursion Sets From Repeated Random Field Observations, With an Application to Climate

S. Sain, Max Sommerfeld, A. Schwartzman, 2018, Journal of the American Statistical Association.

Using the atmospheric CO2 growth rate to constrain the CO2 flux from land use and land cover change since 1900

A. Schwartzman, J. Pongratz, R. Keeling, 2022, Global change biology.

Inverse set estimation and inversion of simultaneous confidence intervals

A. Schwartzman, F. Telschow, Junting Ren, 2022, 2210.03933.

Estimation of linear projections of non-sparse coefficients in high-dimensional regression

A. Schwartzman, David Azriel, 2020, Electronic Journal of Statistics.

On the Explicit Height Distribution and Expected Number of Local Maxima of Isotropic Gaussian Random Fields

A. Schwartzman, Dan Cheng, 2015, 1503.01328.

The Empirical Distribution of a Large Number of Correlated Normal Variables

A. Schwartzman, David Azriel, 2015, Journal of the American Statistical Association.

Method for detecting voxelwise changes in fluorodeoxyglucose-positron emission tomography brain images via background adjustment in cancer clinical trials

Lei Qin, Nezamoddin N. Kachouie, Jeffrey T. Yap, 2017, Journal of medical imaging.

Voxelwise single‐subject analysis of imaging metabolic response to therapy in neuro‐oncology

A. Schwartzman, N. Lin, J. Yap, 2014, Stat.

Analysis of writing in an epilepsy center population: A prospective blinded study

A. Schwartzman, B. Pike, D. Anschel, 2006, Epilepsy & Behavior.

A blinded pilot study of artwork in a comprehensive epilepsy center population

R. Fisher, A. Schwartzman, D. Anschel, 2005, Epilepsy & Behavior.

Spatial confidence sets for raw effect size images

Thomas E. Nichols, A. Schwartzman, Fabian Telschow, 2019, NeuroImage.

Empirical null and false discovery rate analysis in neuroimaging

Jonathan E. Taylor, Robert F. Dougherty, Jongho Lee, 2009, NeuroImage.

Confidence Sets for Cohen’s d effect size images

Thomas E. Nichols, Armin Schwartzman, Alexander Bowring, 2020, NeuroImage.

Paradoxical results of adaptive false discovery rate procedures in neuroimaging studies

Lei Huang, Philip T. Reiss, Erika Proal, 2012, NeuroImage.

Non-Parametric Estimation of a Single Inflection Point in Noisy Observed Signal

Nezamoddin N. Kachouie, A. Schwartzman, A. Schwartzman, 2013 .

Localization of mountain glacier termini in Landsat multi-spectral images

Nezamoddin N. Kachouie, Armin Schwartzman, Peter Huybers, 2013, Pattern Recognit. Lett..

Clinical trial of a farnesyltransferase inhibitor in children with Hutchinson–Gilford progeria syndrome

A. Giobbie-Hurder, D. Neuberg, A. Schwartzman, 2012, Proceedings of the National Academy of Sciences.

Inference for eigenvalues and eigenvectors in exponential families of random symmetric matrices

Armin Schwartzman, Han Na Lee, A. Schwartzman, 2017, J. Multivar. Anal..

Scaling-Rotation Distance and Interpolation of Symmetric Positive-Definite Matrices

David Groisser, Armin Schwartzman, Sungkyu Jung, 2014, SIAM J. Matrix Anal. Appl..

FDR control of detected regions by multiscale matched filtering

Xihong Lin, Nezamoddin N. Kachouie, Armin Schwartzman, 2017, Commun. Stat. Simul. Comput..

Mechanisms of Premature Vascular Aging in Children With Hutchinson-Gilford Progeria Syndrome

A. Giobbie-Hurder, D. Neuberg, A. Schwartzman, 2012, Hypertension.

Bayesian Multivariate Growth Mixture Modeling of Longitudinal Data: An Application to Alzheimer’s Disease Study

W. Thompson, M. Donohue, A. Schwartzman, 2021, bioRxiv.

Biomarker discovery for arsenic exposure using functional data. Analysis and feature learning of mass spectrometry proteomic data.

David C Christiani, Armin Schwartzman, Jaroslaw Harezlak, 2008, Journal of proteome research.

Nonparametric Regression for Estimation of Spatiotemporal Mountain Glacier Retreat From Satellite Images

Nezamoddin N. Kachouie, Armin Schwartzman, Peter Huybers, 2015, IEEE Transactions on Geoscience and Remote Sensing.

Reading impairment in a patient with missing arcuate fasciculus

Lee M. Perry, Robert F. Dougherty, Gayle K. Deutsch, 2009, Neuropsychologia.

Nonparametric two-sample tests on homogeneous Riemannian manifolds, Cholesky decompositions and Diffusion Tensor Image analysis

Leif Ellingson, David Groisser, Vic Patrangenaru, 2013, J. Multivar. Anal..

Comparison of handcrafted features and convolutional neural networks for liver MR image adequacy assessment

Wenyi Lin, Kyle Hasenstab, Guilherme Moura Cunha, 2020, Scientific Reports.

Turbulence-induced 2D correlated image distortion

Yoav Y. Schechner, Marina Alterman, Armin Schwartzman, 2017, 2017 IEEE International Conference on Computational Photography (ICCP).

Fully automated convolutional neural network-based affine algorithm improves liver registration and lesion co-localization on hepatobiliary phase T1-weighted MR images

Claude B. Sirlin, Kang Wang, Alexandra N. Schlein, 2019, European Radiology Experimental.

Distribution of the height of local maxima of Gaussian random fields

Dan Cheng, Armin Schwartzman, A. Schwartzman, 2013, Extremes.

Multiple Testing of Local Maxima for Detection of Unimodal Peaks in 1D

R. Adler, A. Schwartzman, Yulia Gavrilov, 2011 .

MULTIPLE TESTING OF LOCAL MAXIMA FOR DETECTION OF PEAKS IN RANDOM FIELDS.

Dan Cheng, Armin Schwartzman, A. Schwartzman, 2014, Annals of statistics.

Multivariate analysis of eigenvalues and eigenvectors in tensor based morphometry

Natasha Lepore, Xue Hua, Paul Thompson, 2015, Other Conferences.

A deep learning approach to improve retinal structural predictions and aid glaucoma neuroprotective clinical trial design.

A. Schwartzman, L. Zangwill, R. Weinreb, 2022, Ophthalmology. Glaucoma.

Estimating Mountain Glacier Flowlines by Local Linear Regression Gradient Descent

Armin Schwartzman, Kristen Hansen, Kyle Hasenstab, 2021, IEEE Transactions on Geoscience and Remote Sensing.

Coplanar and coaxial orientations of RNA bases and helices.

R. Altman, A. Schwartzman, A. Laederach, 2007, RNA.

Voxelwise multivariate analysis of multimodality magnetic resonance imaging

Norbert Schuff, Armin Schwartzman, Michael Weiner, 2014, Human brain mapping.

Point source detection and false discovery rate control on CMB maps

Domenico Marinucci, Yabebal Fantaye, Javier Carr'on Duque, 2019, Astron. Comput..

Characterizing the DIstribution of Anisotropic MicrO-structural eNvironments with Diffusion-Weighted Imaging (DIAMOND)

Simon K. Warfield, Benoit Scherrer, Sanjay P. Prabhu, 2013, MICCAI.

A simple, consistent estimator of heritability for genome-wide association studies

Rong W. Zablocki, W. Thompson, A. Schork, 2017, bioRxiv.

Glacier Terminus Estimation from Landsat Image Intensity Profiles

Ana-Maria Staicu, Arnab Maity, A. Schwartzman, 2015 .

Spatial confidence regions for combinations of excursion sets in image analysis

Thomas E. Nichols, Armin Schwartzman, Thomas Maullin-Sapey, 2022, Journal of the Royal Statistical Society Series B: Statistical Methodology.

Progeria Syndrome Mechanisms of Premature Vascular Aging in Children with Hutchinson-gilford Progeria Syndrome Methods Study Population and Design

Harvard Medical School, A. Giobbie-Hurder, D. Neuberg, 2022 .

A genericity property of Fr\'{e}chet sample means on Riemannian manifolds

A. Schwartzman, D. Groisser, Sungkyu Jung, 2023, 2309.13823.

Characterizing brain tissue by assessment of the distribution of anisotropic microstructural environments in diffusion‐compartment imaging (DIAMOND)

A. Schwartzman, S. Warfield, B. Scherrer, 2016, Magnetic resonance in medicine.

Nonparametric bootstrap of sample means of positive-definite matrices with an application to diffusion-tensor-imaging data analysis

Leif Ellingson, David Groisser, Vic Patrangenaru, 2017, Commun. Stat. Simul. Comput..

Functional delta residuals and applications to simultaneous confidence bands of moment based statistics

A. Schwartzman, F. Telschow, Samuel Davenport, 2020, J. Multivar. Anal..

Functional delta residuals and applications to functional effect sizes

A. Schwartzman, F. Telschow, Samuel Davenport, 2020 .