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- Post-stratified importance sampling
- Scalable Bayesian inference for time-discretised Markov jump processes via exchangeable particle Gibbs
- Post-Inference Model Chaining: A Problem Statement and a Model-based Bootstrap for Training End-to-End Digital Twins
- The Hidden Markov Ising Model with Exogenous Covariates
- Privacy for Free in Efficient Agnostic Halfspace Learning
- Exact association-test distributions for prior-informed stepwise SNP prioritization
- Estimating Treatment Effects with a Single Arm Clinical Trial and Data Summaries from an External Control Group: is it Possible?
- Exact Selective Inference for Spectral Clustering via Piecewise-Constant Graph Perturbation
- Amortized Nonlinear Variable Selection with Prior-Data Fitted Networks
- UniFlow: Unified Multi-Scale Flow Matching for Time Series Generation
- Bayesian Cluster-Adjusted Standardised Mean Differences: A Simulation Study
- Where Is the Truth When AI Agents Disagree? Dependence-Aware Belief Propagation for Unsupervised Truth Discovery (Extended Version)
- Selection instability and coefficient uncertainty in Cox modelling after Lasso selection
- One-shot Distributed Learning via Weighted Averaging with Server-side Information
- Bayesian Change-Point Detection and Fault Scoring in District Heating Systems
- Directional Statistics in Signal Processing: A Geometry Driven Overview of Models, Learning, and Applications
- Conditional independence and graphical models for rankings
- A reliability data aggregation method for fusion-oriented research facilities
- Identifying the determinants of soccer coach turnover by competing risks models: a case study on Italian League Serie A
- Bandwidth rules for Dirichlet kernel density estimation on the simplex
- When Listwise Deletion Works: Causal Diagrams and Complete-Case Regression
- Analytically Calibrated Upper L-Statistics for High-Dimensional Mean Change-Point Testing
- Proper Agnostic Learning of Affine Halfspaces under Log-Concave Marginals
- Nearly Linear-Time Follow-the-Perturbed-Leader for Weakly Observable Graph Bandits
- Covariate Adjustment for Time-Restricted Marginal Win Statistics in Randomized Trials: Assumption-Lean Inference and Guaranteed Efficiency Gain