Bayesian analysis of transcriptomic and genomic data
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A hierarchical physiologically-based pharmacokinetic modeling platform for genetic and exposure effects in metabolic pathways
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Model selection principles and false discovery rate control
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Using multi-level Bayesian hierarchical model to detect related multiple SNPs within multiple genes to disease risk
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A novel hybrid probabilistic framework for model validation
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Statistical methods for causal inference and densely dependent random sums
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Statistical learning in High Dimensions: Interpretability, inference and applications
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Bayesian inference using Markov chain Monte Carlo methods in pharmacokinetic /pharmacodynamic systems analysis
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Reproducible large-scale inference in high-dimensional nonlinear models
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Large-scale multiple hypothesis testing and simultaneous inference: compound decision theory and data driven procedures
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Large scale inference with structural information
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Leveraging sparsity in theoretical and applied machine learning and causal inference
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Statistical approaches for inferring category knowledge from social annotation
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Do humans play dice: choice making with randomization
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Enhancing model performance of regularization methods by incorporating prior information
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Learning fair models with biased heterogeneous data
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Sense and sensibility: statistical techniques for human energy expenditure estimation using kinematic sensors
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Characterization and discovery of genetic associations: multiethnic fine-mapping and incorporation of functional information
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Depth inference and visual saliency detection from 2D images
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Computational model of stroke therapy and long term recovery
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Filling in the gaps: 3D mapping Arizona's Basin and Range aquifer in the Prescott Active Management Area
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Data-driven optimization for indoor localization
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Biometric models of psychopathic traits in adolescence: a comparison of item-level and sum-score approaches
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Exploring threats to causal inference in empirical education research
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Sharpening the edge of tools for microbial diversity analysis
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