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2. Abstractions for Probabilistic Programming to Support Model Development
3. Accurate and Sensitive Quantification of Protein-DNA Binding Affinity
4. A Cognitively Diagnostic Modeling Approach to Diagnosing Misconceptions and Subskills
5. A Computational Perspective of Causal Inference and the Data Fusion Problem
6. Advances in Credit Risk Modeling
7. Advances in Deep Generative Modeling With Applications to Image Generation and Neuroscience
8. Advances in Machine Learning for Complex Structured Functional Data
9. Advances in Machine Learning for Compositional Data
10. Advances in Model Selection Techniques with Applications to Statistical Network Analysis and Recommender Systems
11. Advances in Non-Stationary Sequential Decision-Making
12. Advances in Statistical Machine Learning Methods for Neural Data Science
13. A Geometric Approach to Dynamical System: Global Analysis for Non-Convex Optimization
14. A Graphon-based Framework for Modeling Large Networks
15. A Hypothesis Testing Procedure Designed for Q-Matrix Validation of Diagnostic Classification Models
16. Analyzing Hierarchical Data with the DINA-HC Approach
17. An Assortment of Unsupervised and Supervised Applications to Large Data
18. An Item Response Theory Approach to Causal Inference in the Presence of a Pre-intervention Assessment
19. A Point Process Model for the Dynamics of Limit Order Books
20. Application of Distance Covariance to Extremes and Time Series and Inference for Linear Preferential Attachment Networks
21. Application of Distance Covariance to Time Series Modeling and Assessing Goodness-of-Fit
22. Application of ordered latent class regression model in educational assessment
23. Applications of Modern Statistical Mechanics: Molecular Transport and Statistical Learning
24. Asymptotic Theory and Applications of Random Functions
25. A Three-Paper Dissertation on Longitudinal Data Analysis in Education and Psychology
26. A unified view of high-dimensional bridge regression
27. Bayesian Modeling Strategies for Complex Data Structures, with Applications to Neuroscience and Medicine
28. Bayesian Model Selection in terms of Kullback-Leibler discrepancy
29. Bayesian Multidimensional Scaling Model for Ordinal Preference Data
30. Beyond summary statistics: extracting etiological insights from genome-wide association cohorts
31. Blessing of Dependence and Distribution-Freeness in Statistical Hypothesis Testing
32. Can a Test Measure Teaching Quality? Validity of Mexico’s Teacher Entry Examination After the 2013 Education Reform
33. Causal Mediation Analysis for Effect Heterogeneity
34. Characterization of the Fluctuations in a Symmetric Ensemble of Rank-Based Interacting Particles
35. Cognitive Diagnostic Models-based Automatic Item Generation: Item Feature Exploration and Calibration Model Selection
36. Community Detection in Social Networks: Multilayer Networks and Pairwise Covariates
37. Contagion and Systemic Risk in Financial Networks
38. Contributions to Semiparametric Inference to Biased-Sampled and Financial Data
39. Convex Optimization Algorithms and Recovery Theories for Sparse Models in Machine Learning
40. Cooperative Sequential Hypothesis Testing in Multi-Agent Systems
41. Credit Risk Modeling and Analysis Using Copula Method and Changepoint Approach to Survival Data
42. Daily Vitamin D3 Supplementation as a Treatment for Health Disparities
43. Data-Driven Quickest Change Detection
44. Decoding Starlight with Big Survey Data, Machine Learning, and Cosmological Simulations
45. Deconstructing Spinal Interneurons, one cell type at a time
46. Deconvolution Problems for Structured Sparse Signal
47. Deep Probabilistic Graphical Modeling
48. Detecting Dependence Change Points in Multivariate Time Series with Applications in Neuroscience and Finance
49. Developing an approach to determine generalizability: A review of efficacy and effectiveness trials funded by the Institute of Education Sciences
50. Developing Statistical Methods for Incorporating Complexity in Association Studies
51. Diagnostic Classification Modeling of Rubric-Scored Constructed-Response Items
52. Distributionally Robust Optimization and its Applications in Machine Learning
53. Distributionally Robust Performance Analysis with Applications to Mine Valuation and Risk
54. Dynamics of Large Rank-Based Systems of Interacting Diffusions
55. Dynamic Targeted Pricing in B2B Settings
56. Efficiency in Lung Transplant Allocation Strategies
57. Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries
58. Empirical Bayes, Bayes factors and deoxyribonucleic acid fingerprinting
59. Essays in Applied Econometrics and Labor Economics
60. Essays in Cluster Sampling and Causal Inference
61. Essays in Econometrics
62. Essays in High Dimensional Time Series Analysis
63. Essays on Demand Estimation, Financial Economics and Machine Learning
64. Essays on Matching and Weighting for Causal Inference in Observational Studies
65. Essays on Simulation-Based Estimation
66. Estimating the Q-matrix for Cognitive Diagnosis Models in a Bayesian Framework
67. Estimation and Testing Methods for Monotone Transformation Models
68. Estimation of Q-matrix for DINA Model Using the Constrained Generalized DINA Framework
69. Event History Analysis in Multivariate Longitudinal Data
70. Exact simulation algorithms with applications in queueing theory and extreme value analysis
71. Exact Simulation Techniques in Applied Probability and Stochastic Optimization
72. Ex-Communist Party Choices and the Electoral Success of the Radical Right in Central and Eastern Europe
73. Expansion of a filtration with a stochastic process: a high frequency trading perspective
74. Exploring a Generalizable Machine Learned Solution for Early Prediction of Student At-Risk Status
75. Extreme Storm Surge Hazard Estimation and Windstorm Vulnerability Assessment for Quantitative Risk Analysis
76. Extreme Storm Surge Return Period Prediction Using Tidal Gauge Data and Estimation of Damage to Structures from Storm-Induced Wind Speed in South Korea
77. Feature Selection for High Dimensional Causal Inference
78. Flexible Regression Models for Estimating Interactions between a Treatment and Scalar/Functional Predictors
79. Flexible Sparse Learning of Feature Subspaces
80. Generalized Volatility-Stabilized Processes
81. Generative Modeling and Inference in Directed and Undirected Neural Networks
82. High-dimensional Asymptotics for Phase Retrieval with Structured Sensing Matrices
83. High-dimensional asymptotics: new insights and methods
84. Human Papillomavirus Vaccination, Online Health Information Seeking, and Health Literacy among Transgender and Gender Nonbinary People
85. Hydroclimatology of Extreme Precipitation and Floods Originating from the North Atlantic Ocean
86. Identification and Validation of Structures in Neural Population Responses
87. Identifying and Targeting Master Regulators of Drug Resistance in Lung Adenocarcinoma through Network Analysis of Tumor Transcriptomic Data
88. Inference in ERGMs and Ising Models.
89. Inference of functional neural connectivity and convergence acceleration methods
90. Interaction-Based Learning for High-Dimensional Data with Continuous Predictors
91. Kernel-based association measures
92. Large Dimensional Data Analysis using Orthogonally Decomposable Tensors: Statistical Optimality and Computational Tractability
93. Latent Variable Modeling and Statistical Learning
94. Latent Variable Models for Events on Social Networks
95. Latent Variable Models in Measurement: Theory and Application
96. Learning predictive models from menstrual cycle data
97. Learning Structure in Time Series for Neuroscience and Beyond
98. Limit theorems beyond sums of I.I.D observations
99. Limit Theory for Spatial Processes, Bootstrap Quantile Variance Estimators, and Efficiency Measures for Markov Chain Monte Carlo
100. Linear Constraints in Optimal Transport
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