Search Results - "Lee, Ann B."
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A composite likelihood approach for inference under photometric redshift uncertainty
Published in Monthly notices of the Royal Astronomical Society (01-02-2022)“…ABSTRACT Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid,…”
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Discovering genetic ancestry using spectral graph theory
Published in Genetic epidemiology (01-01-2010)“…As one approach to uncovering the genetic underpinnings of complex disease, individuals are measured at a large number of genetic variants (usually SNPs)…”
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An Optimal Transportation Approach for Nuclear Structure-Based Pathology
Published in IEEE transactions on medical imaging (01-03-2011)“…Nuclear morphology and structure as visualized from histopathology microscopy images can yield important diagnostic clues in some benign and malignant tissue…”
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The Nonlinear Statistics of High-Contrast Patches in Natural Images
Published in International journal of computer vision (01-08-2003)“…Issue Title: Special Issue on Computational Vision at Brown University Recently, there has been a great deal of interest in modeling the non-Gaussian…”
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On the Use of General Control Samples for Genome-wide Association Studies: Genetic Matching Highlights Causal Variants
Published in American journal of human genetics (01-02-2008)“…Resources being amassed for genome-wide association (GWA) studies include “control databases” genotyped with a large-scale SNP array. How to use these…”
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Occlusion Models for Natural Images: A Statistical Study of a Scale-Invariant Dead Leaves Model
Published in International journal of computer vision (01-01-2001)“…We develop a scale-invariant version of Matheron's "dead leaves model" for the statistics of natural images. The model takes occlusions into account and…”
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ABC-CDE: Toward Approximate Bayesian Computation With Complex High-Dimensional Data and Limited Simulations
Published in Journal of computational and graphical statistics (03-07-2019)“…Approximate Bayesian computation (ABC) is typically used when the likelihood is either unavailable or intractable but where data can be simulated under…”
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Nonparametric Conditional Density Estimation in a High-Dimensional Regression Setting
Published in Journal of computational and graphical statistics (01-10-2016)“…In some applications (e.g., in cosmology and economics), the regression is not adequate to represent the association between a predictor x and a response Z…”
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Converting high-dimensional regression to high-dimensional conditional density estimation
Published in Electronic journal of statistics (01-01-2017)Get full text
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Non-Gaussianity in the weak lensing correlation function likelihood – implications for cosmological parameter biases
Published in Monthly notices of the Royal Astronomical Society (01-12-2020)“…ABSTRACT We study the significance of non-Gaussianity in the likelihood of weak lensing shear two-point correlation functions, detecting significantly non-zero…”
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Most genetic risk for autism resides with common variation
Published in Nature genetics (01-08-2014)“…Joseph Buxbaum and colleagues use an epidemiological sample from Sweden to investigate the genetic architecture of autism spectrum disorders. They conclude…”
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Unlocking GOES: A Statistical Framework for Quantifying the Evolution of Convective Structure in Tropical Cyclones
Published in Journal of applied meteorology and climatology (01-10-2020)“…Tropical cyclones (TCs) rank among the most costly natural disasters in the United States, and accurate forecasts of track and intensity are critical for…”
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A SPECTRAL GRAPH APPROACH TO DISCOVERING GENETIC ANCESTRY
Published in The annals of applied statistics (01-03-2010)“…Mapping human genetic variation is fundamentally interesting in fields such as anthropology and forensic inference. At the same time, patterns of genetic…”
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Diffusion maps and coarse-graining: a unified framework for dimensionality reduction, graph partitioning, and data set parameterization
Published in IEEE transactions on pattern analysis and machine intelligence (01-09-2006)“…We provide evidence that nonlinear dimensionality reduction, clustering, and data set parameterization can be solved within one and the same framework. The…”
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A spectral series approach to high-dimensional nonparametric regression
Published in Electronic journal of statistics (01-01-2016)Get full text
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Prevalence, risk factors, and surveillance patterns for gastric intestinal metaplasia among patients undergoing upper endoscopy with biopsy
Published in Gastrointestinal endoscopy (01-01-2020)“…Gastric intestinal metaplasia (GIM) is an important precursor lesion to gastric cancer (GC), the second leading cause of cancer death worldwide. There exist…”
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Upper-ocean changes with hurricane-strength wind events: a study using Argo profiles and an ocean reanalysis
Published in Ocean science (05-11-2024)“…As the Earth's climate warms, the intensity and rain rate of tropical cyclones (TCs) is projected to increase. TCs intensify by extracting heat energy from the…”
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Treelets: An Adaptive Multi-Scale Basis for Sparse Unordered Data
Published in The annals of applied statistics (01-06-2008)“…In many modem applications, including analysis of gene expression and text documents, the data are noisy, high-dimensional, and unordered-with no particular…”
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Spatiotemporal methods for estimating subsurface ocean thermal response to tropical cyclones
Published in Advances in statistical climatology, meteorology and oceanography (22-07-2024)“…Tropical cyclones (TCs), driven by heat exchange between the air and sea, pose a substantial risk to many communities around the world. Accurate…”
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Spectral Connectivity Analysis
Published in Journal of the American Statistical Association (01-09-2010)“…Spectral kernel methods are techniques for mapping data into a coordinate system that efficiently reveals the geometric structure-in particular, the…”
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