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- Risk-Aware Output Control Should be the Focus of Machine Unlearning
- Conformal Novelty Detection via Data-enhanced Localization
- Breakdown-Resistant Hierarchical Bayesian Calibration for Multi-Center Clinical Trials
- Accuracy and efficiency of compact foundation models for surface-water mapping during floods
- Cross-vehicle injury spillovers of ADAS functions in two-vehicle rear-end and same-direction sideswipe crashes
- The Noise-Transmission Burden of Diffusion Network: Why Image Prediction Can Outperform Noise Prediction
- Performance Guarantees for Permissionless Lending
- Adaptive Probe Design for Auditing AI Agents
- Designing Customer Feedback for Subscription Boxes
- Intervene, Calibrate, Discover: Learning Causal Structure from Pixels
- Intrinsic Information Rates of Summaries in Simulation-Based Inference
- Pro-Active Inference
- Heterogeneity and Subgrouping in Modern Statistics and AI
- The Effect of Residual Confounding in the Analysis of Large Observational Data Sets
- Semiparametric inference for a Target Outcome Leveraging Heterogeneous External Summaries of Auxiliary Outcomes
- Width and Depth Limits Commute During Training in Linear Residual Networks
- Vector Copula-Based Markov Models
- Announced Breaks Separate Conformal Reliability from Frequency Calibration
- SNACK: A Sequential Notation Framework for Probabilistic Graph Generation
- Latent-driven Imputation and Forecasting for partially observed Time Series (LIFTS)
- Bayesian Generalized Network Autoregressive Model with Structured Shrinkage and Persistence Priors
- Bias-robust causal inference for panel data
- High-Dimensional Change Point Analysis for Temporally Dependent Data
- Divide et Calibra: Multiclass Local Calibration via Vector Quantization
- Median Radial Function: A Robust, Covariance-Free Framework and Applications