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2. Variational Bayesian Methods for Inferring Spatial Statistics and Nonlinear Dynamics
3. Using neuroimaging to investigate the effect of expertise in rapid perceptual decision making
4. Use of External Representations in Reasoning about Causality
5. Understanding the Nature of Stellar Chemical Abundance Distributions in Nearby Stellar Systems
6. Uncertainty Quantification in Data-Driven Simulation and Optimization: Statistical and Computational Efficiency
7. Uncertainty Quantification in Composite Materials
8. Unbiased Penetrance Estimates with Unknown Ascertainment Strategies
9. Two Papers of Financial Engineering Relating to the Risk of the 2007--2008 Financial Crisis
10. Tropical Cyclone Risk Assessment Using Statistical Models
11. Training Decision Trees for Optimal Decision-Making
12. Toward a scalable Bayesian workflow
13. Toward Annotation Efficiency in Biased Learning Settings for Natural Language Processing
14. Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology
15. Time Series Modeling with Shape Constraints
16. Three New Studies on Model-data Fit for Latent Variable Models in Educational Measurement
17. Three Contributions to Latent Variable Modeling
18. The Relation between Uncertainty in Latent Class Membership and Outcomes in a Latent Class Signal Detection Model
19. The Ordered Latent Transition Analysis Model for the Measurement of Learning
20. The MNL-Bandit Problem: Theory and Applications
21. The emergence of the data science profession
22. The Cognitive and Demographic Variables that Underlie Notetaking and Review in Mathematics: Does Quality of Notes Predict Test Performance in Mathematics?
23. The Centrality of Sadness: Networks of Depression, Grief, and Trauma Symptoms in a Spousally Bereaved Sample
24. Studies of Extensions of HRM-SDT for Constructed Responses
25. Structured Tensor Recovery and Decomposition
26. Stochastic Models of Limit Order Markets
27. Stochastic Differential Equations and Strict Local Martingales
28. Statistics for Learning Genetics
29. Statistical Perspectives on Modern Network Embedding Methods
30. Statistical modeling and statistical learning for disease prediction and classification
31. Statistical Methods for Structured Data: Analyses of Discrete Time Series and Networks
32. Statistical Methods for Modeling Progression and Learning Mechanisms of Neuropsychiatric Disorders
33. Statistical Methods for Modeling Biomarkers of Neuropsychiatric Diseases
34. Statistical Methods for Integrated Cancer Genomic Data Using a Joint Latent Variable Model
35. Statistical methods for indirectly observed network data
36. Statistical Methods for Genetic Studies with Family History of Diseases
37. Statistical Methods for Epigenetic Data
38. Statistical Machine Learning Methods for the Large Scale Analysis of Neural Data
39. Statistical Machine Learning Methods for High-dimensional Neural Population Data Analysis
40. Statistical Learning for Process Data
41. Statistical inference in two non-standard regression problems
42. Statistical Inference for Diagnostic Classification Models
43. Statistical Inference and Experimental Design for Q-matrix Based Cognitive Diagnosis Models
44. Statistical approach to tagging stellar birth groups in the Milky Way
45. Statistical Analysis of Complex Data in Survival and Event History Analysis
46. State-Space Models and Latent Processes in the Statistical Analysis of Neural Data
47. Spectral Filtering for Spatio-temporal Dynamics and Multivariate Forecasts
48. Sparse selection in Cox models with functional predictors
49. Some Statistical Models for Prediction
50. Some Nonparametric Methods for Clinical Trials and High Dimensional Data
51. Some Models for Time Series of Counts
52. Single Channel auditory source separation with neural network
53. Sequential Rerandomization in the Context of Small Samples
54. Sequential Decision Making with Combinatorial Actions and High-Dimensional Contexts
55. Semiparametric inference with shape constraints
56. Semiparametric Inference of Censored Data with Time-dependent Covariates
57. Semiparametric Estimation of a Gaptime-Associated Hazard Function
58. Self-controlled methods for postmarketing drug safety surveillance in large-scale longitudinal data
59. Selected Legal Applications for Bayesian Methods
60. Scalable Community Detection in Massive Networks using Aggregated Relational Data
61. Robust Statistical Approaches Dealing with High-Dimensional Observational Data
62. Rents, Patronage, and Defection: State-building and Insurgency in Afghanistan
63. Rater Drift in Constructed Response Scoring via Latent Class Signal Detection Theory and Item Response Theory
64. Random Walk Models, Preferential Attachment, and Sequential Monte Carlo Methods for Analysis of Network Data
65. Property Testing and Probability Distributions: New Techniques, New Models, and New Goals
66. Process Data Applications in Educational Assessment
67. Probabilistic Programming for Deep Learning
68. Privacy-Aware Data Analysis: Recent Developments for Statistics and Machine Learning
69. Predicting Autonomous Promoter Activity Based on Genome-wide Modeling of Massively Parallel Reporter Data
70. Population Genetics of Identity By Descent
71. Point Process Models for Heterogeneous Event Time Data
72. Phase retrieval in the high-dimensional regime
73. Penalized Joint Maximum Likelihood Estimation Applied to Two Parameter Logistic Item Response Models
74. Partition-based Model Representation Learning
75. Overlapping Communities on Large-Scale Networks: Benchmark Generation and Learning via Adaptive Stochastic Optimization
76. Optimization Foundations of Reinforcement Learning
77. Optimization Algorithms for Structured Machine Learning and Image Processing Problems
78. On the Multiway Principal Component Analysis
79. On the Construction of Minimax Optimal Nonparametric Tests with Kernel Embedding Methods
80. On testing the change-point in the longitudinal bent line quantile regression model
81. On Recovering the Best Rank-? Approximation from Few Entries
82. On Model-Selection and Applications of Multilevel Models in Survey and Causal Inference
83. On Identifying Rare Variants for Complex Human Traits
84. Nonlinear penalized estimation of true Q-matrix in cognitive diagnostic models
85. New perspectives on learning, inference, and control in brains and machines
86. New perspectives in cross-validation
87. Multiple Imputation for Handling Missing Data of Covariates in Meta-Regression
88. Multiple Causal Inference with Bayesian Factor Models
89. Modern Statistical/Machine Learning Techniques for Bio/Neuro-imaging Applications
90. Modernizing Markov Chains Monte Carlo for Scientific and Bayesian Modeling
91. Modelling Conditional Dependence Between Response Time and Accuracy in Cognitive Diagnostic Models
92. Modeling the Likelihood of Construction Incidents Using Public Data
93. Modeling Strategies for Large Dimensional Vector Autoregressions
94. Modeling Random Events
95. Mixed Methods for Mixed Models
96. Minimax-inspired Semiparametric Estimation and Causal Inference
97. Methods in functional data analysis and functional genomics
98. Methods for Personalized and Evidence Based Medicine
99. Methods for handling measurement error and sources of variation in functional data models
100. Methods for functional regression and nonlinear mixed-effects models with applications to PET data
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