Search Results
2. Inference in ERGMs and Ising Models.
3. Large Dimensional Data Analysis using Orthogonally Decomposable Tensors: Statistical Optimality and Computational Tractability
4. Martingale Schrodinger Bridges and Optimal Semistatic Portfolios
5. On the Multiway Principal Component Analysis
6. Optimal Inference with a Multidimensional Multiscale Statistic
7. Process Data Applications in Educational Assessment
8. Signal-to-noise ratio aware minimaxity and its asymptotic expansion
9. Statistical Methods for Structured Data: Analyses of Discrete Time Series and Networks
10. Advances in Machine Learning for Complex Structured Functional Data
11. Advances in Machine Learning for Compositional Data
12. Blessing of Dependence and Distribution-Freeness in Statistical Hypothesis Testing
13. Latent Variable Models for Events on Social Networks
14. Modeling Random Events
15. Modernizing Markov Chains Monte Carlo for Scientific and Bayesian Modeling
16. On Recovering the Best Rank-? Approximation from Few Entries
17. Overlapping Communities on Large-Scale Networks: Benchmark Generation and Learning via Adaptive Stochastic Optimization
18. Statistical approach to tagging stellar birth groups in the Milky Way
19. Statistical Perspectives on Modern Network Embedding Methods
20. Advances in Statistical Machine Learning Methods for Neural Data Science
21. Characterization of the Fluctuations in a Symmetric Ensemble of Rank-Based Interacting Particles
22. Event History Analysis in Multivariate Longitudinal Data
23. High-dimensional Asymptotics for Phase Retrieval with Structured Sensing Matrices
24. On the Construction of Minimax Optimal Nonparametric Tests with Kernel Embedding Methods
25. Phase retrieval in the high-dimensional regime
26. Semiparametric Inference of Censored Data with Time-dependent Covariates
27. Statistical Learning for Process Data
28. Toward a scalable Bayesian workflow
29. Community Detection in Social Networks: Multilayer Networks and Pairwise Covariates
30. Deep Probabilistic Graphical Modeling
31. High-dimensional asymptotics: new insights and methods
32. Latent Variable Models in Measurement: Theory and Application
33. Multiple Causal Inference with Bayesian Factor Models
34. New perspectives in cross-validation
35. Partition-based Model Representation Learning
36. Some Statistical Models for Prediction
37. Statistical Analysis of Complex Data in Survival and Event History Analysis
38. Time evolution of the Kardar-Parisi-Zhang equation
39. Advances in Deep Generative Modeling With Applications to Image Generation and Neuroscience
40. Essays in High Dimensional Time Series Analysis
41. Limit theorems beyond sums of I.I.D observations
42. Linear Constraints in Optimal Transport
43. Meta-analysis of expression and methylation signatures indicates a stress-related epigenetic mechanism in multiple neuropsychiatric disorders
44. Point Process Models for Heterogeneous Event Time Data
45. Scalable Community Detection in Massive Networks using Aggregated Relational Data
46. Analysis of genotype by methylation interactions through sparsity-inducing regularized regression
47. Application of Distance Covariance to Extremes and Time Series and Inference for Linear Preferential Attachment Networks
48. Bayesian hierarchical vector autoregressive models for patient-level predictive modeling
49. Bayesian Modeling Strategies for Complex Data Structures, with Applications to Neuroscience and Medicine
50. Bifurcation analysis of two coupled Jansen-Rit neural mass models
51. Causal modeling in a multi-omic setting: insights from GAW20
52. Community-based benchmarking improves spike rate inference from two-photon calcium imaging data
53. Coping with family structure in genome-wide association studies: a comparative evaluation
54. Different population dynamics in the supplementary motor area and motor cortex during reaching
55. Efficient and accurate extraction of in vivo calcium signals from microendoscopic video data
56. Essays in Cluster Sampling and Causal Inference
57. Minimax-inspired Semiparametric Estimation and Causal Inference
58. Neyman-Pearson classification algorithms and NP receiver operating characteristics
59. Readmission prediction via deep contextual embedding of clinical concepts
60. Scoring Model Predictions using Cross-Validation
61. Selected Legal Applications for Bayesian Methods
62. Statistical Machine Learning Methods for the Large Scale Analysis of Neural Data
63. Stochastic Differential Equations and Strict Local Martingales
64. The challenge of detecting genotype-by-methylation interaction: GAW20
65. Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology
66. A continuous morphological approach to study the evolution of pollen in a phylogenetic context: An example with the order Myrtales
67. Advances in Credit Risk Modeling
68. A unified view of high-dimensional bridge regression
69. Body size and hosts of Triatoma infestans populations affect the size of bloodmeal contents and female fecundity in rural northwestern Argentina
70. Distributionally Robust Optimization and its Applications in Machine Learning
71. Distributionally Robust Performance Analysis with Applications to Mine Valuation and Risk
72. Efficient Estimation of the Expectation of a Latent Variable in the Presence of Subject-Specific Ancillaries
73. Electrical stimulus artifact cancellation and neural spike detection on large multi-electrode arrays
74. Empirical Bayes, Bayes factors and deoxyribonucleic acid fingerprinting
75. Essays on Matching and Weighting for Causal Inference in Observational Studies
76. Expansion of a filtration with a stochastic process: a high frequency trading perspective
77. Fast online deconvolution of calcium imaging data
78. Flexible Sparse Learning of Feature Subspaces
79. Multi-scale approaches for high-speed imaging and analysis of large neural populations
80. Random Walk Models, Preferential Attachment, and Sequential Monte Carlo Methods for Analysis of Network Data
81. Statistical Machine Learning Methods for High-dimensional Neural Population Data Analysis
82. The Prior Can Often Only Be Understood in the Context of the Likelihood
83. Time Series Modeling with Shape Constraints
84. Advances in Model Selection Techniques with Applications to Statistical Network Analysis and Recommender Systems
85. Asymptotic Theory and Applications of Random Functions
86. Latent Variable Modeling and Statistical Learning
87. Machine learning and data mining in complex genomic data a review on the lessons learned in Genetic Analysis Workshop Nineteen
88. Measuring Spatial Extremal Dependence
89. Methods for Personalized and Evidence Based Medicine
90. On Model-Selection and Applications of Multilevel Models in Survey and Causal Inference
91. R codes for "Sparse Vector Autoregressive Modeling" by Davis, Zang and Zheng (2016)
92. Semiparametric inference with shape constraints
93. Spectral Filtering for Spatio-temporal Dynamics and Multivariate Forecasts
94. Tensor Analysis Reveals Distinct Population Structure that Parallels the Different Computational Roles of Areas M1 and V1
95. A Generalizable Brain-Computer Interface (BCI) Using Machine Learning for Feature Discovery
96. A Graphon-based Framework for Modeling Large Networks
97. An Assortment of Unsupervised and Supervised Applications to Large Data
98. Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral Inhibition
99. Efficiency in Lung Transplant Allocation Strategies
100. GLMLE: graph-limit enabled fast computation for fitting exponential random graph models to large social networks
- « Previous
- Next »
- 1
- 2
- 3