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- Sampling Design and Confidence Tubes for Integral Curves on Riemannian Manifolds
- Model-Based Learning of Latent Euclidean Embedding from Relational Data
- Causal Record Linkage
- Pricing Today, Shaping Tomorrow: Contextual Dynamic Pricing in Purchase-Driven Evolving Systems
- Nonnegativity Shapes Predictive Uncertainty: Complementary Model Fits and Quantile Construction
- Representative Learning for Distributed Support Vector Machines
- Movement based social interactions with label uncertainty
- Artificial Intelligence in Pharmaceutical Development: Building Rigorous, Decision-Ready Evidence
- Efficient Causal Survival Inference under Limited Surrogate Monitoring
- Characterizing Estimator-Regime Transitions in Adaptive Enrichment Trials
- Robust Inference for Spiked Eigenspace under Elliptical Distributions
- Time-Specific Multinomial Logistic Regression for Competing Risks
- Where Causal Discovery Breaks on Real Data: Measuring the Assumptions One Property at a Time
- Power-Optimal Risk Control via Standardized Margin Calibration
- Guide to Teaching with Data in Statistics and Data Science Classrooms
- Penalized Likelihood Inference in Highly Multivariate Sparse Spectral Graphical Gaussian Processes
- Statistical Inference under Performativity: From Policy Feedback to Self-Evolving Systems
- Vector incremental treatment effects
- Transformer-Based Reinforcement Learning for Phase I Dose Allocation
- Statistical Sheaf Modeling Methods for Measuring Qualia Structures
- Robust Estimation of Prior Parameters in Normal-Normal Empirical Bayes
- Decomposition Atlases of Brains and Kidneys from Postmortem CT: Shape and Topological Data Analysis
- Outstrumental Variable Regression
- KINDER: Kernel-based Independence for Fair Representation Learning via Prototype-space Erasure
- A Beta-Based Heteroskedasticity-Consistent Covariance Matrix Estimator