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2. Advances in Machine Learning for Complex Structured Functional Data
3. Advances in Machine Learning for Compositional Data
4. Blessing of Dependence and Distribution-Freeness in Statistical Hypothesis Testing
5. Latent Variable Models for Events on Social Networks
6. Modeling Random Events
7. Modernizing Markov Chains Monte Carlo for Scientific and Bayesian Modeling
8. On Recovering the Best Rank-? Approximation from Few Entries
9. Overlapping Communities on Large-Scale Networks: Benchmark Generation and Learning via Adaptive Stochastic Optimization
10. Statistical approach to tagging stellar birth groups in the Milky Way
11. Statistical Perspectives on Modern Network Embedding Methods
12. Advances in Statistical Machine Learning Methods for Neural Data Science
13. Characterization of the Fluctuations in a Symmetric Ensemble of Rank-Based Interacting Particles
14. Event History Analysis in Multivariate Longitudinal Data
15. High-dimensional Asymptotics for Phase Retrieval with Structured Sensing Matrices
16. On the Construction of Minimax Optimal Nonparametric Tests with Kernel Embedding Methods
17. Phase retrieval in the high-dimensional regime
18. Semiparametric Inference of Censored Data with Time-dependent Covariates
19. Statistical Learning for Process Data
20. Toward a scalable Bayesian workflow
21. Community Detection in Social Networks: Multilayer Networks and Pairwise Covariates
22. Deep Probabilistic Graphical Modeling
23. High-dimensional asymptotics: new insights and methods
24. Latent Variable Models in Measurement: Theory and Application
25. Multiple Causal Inference with Bayesian Factor Models
26. New perspectives in cross-validation
27. Partition-based Model Representation Learning
28. Some Statistical Models for Prediction
29. Statistical Analysis of Complex Data in Survival and Event History Analysis
30. Advances in Deep Generative Modeling With Applications to Image Generation and Neuroscience
31. Essays in High Dimensional Time Series Analysis
32. Limit theorems beyond sums of I.I.D observations
33. Linear Constraints in Optimal Transport
34. Point Process Models for Heterogeneous Event Time Data
35. Scalable Community Detection in Massive Networks using Aggregated Relational Data
36. Application of Distance Covariance to Extremes and Time Series and Inference for Linear Preferential Attachment Networks
37. Bayesian Modeling Strategies for Complex Data Structures, with Applications to Neuroscience and Medicine
38. Bifurcation analysis of two coupled Jansen-Rit neural mass models
39. Causal modeling in a multi-omic setting: insights from GAW20
40. Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data
41. Essays in Cluster Sampling and Causal Inference
42. Minimax-inspired Semiparametric Estimation and Causal Inference
43. Neyman-Pearson classification algorithms and NP receiver operating characteristics
44. Scoring Model Predictions using Cross-Validation
45. Selected Legal Applications for Bayesian Methods
46. Statistical Machine Learning Methods for the Large Scale Analysis of Neural Data
47. Stochastic Differential Equations and Strict Local Martingales
48. Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology
49. A continuous morphological approach to study the evolution of pollen in a phylogenetic context: An example with the order Myrtales
50. Advances in Credit Risk Modeling
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