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1,205 records
- Accelerated Regularized Wasserstein Proximal Sampling Algorithms
- Model selection by cross-validation in an expectile linear regression
- Permutation Inference under Multi-way Clustering and Missing Data
- Semiparametric Efficient Data Integration Using the Dual-Frame Sampling Framework
- Tail-Sensitive KL and Rényi Convergence of Unadjusted Hamiltonian Monte Carlo via One-Shot Couplings
- Optimal Transport under Group Fairness Constraints
- Multi-environment Invariance Learning with Missing Data
- Robust Bayesian Inference via Variational Approximations of Generalized Rho-Posteriors
- Characterization of multi-way binary tables with uniform margins and fixed correlations
- Inference for Multiple Change-points in Piecewise Locally Stationary Time Series
- Extensions of the solidarity principle of the spectral gap for Gibbs samplers to their blocked and collapsed variants
- Constrained Density Estimation via Optimal Transport
- Robust Mean Estimation under Quantization
- Inference-Time Alignment for Diffusion Models via Variationally Stable Doob's Matching
- Censored Graphical Horseshoe: Bayesian sparse precision matrix estimation with censored and missing data
- A brief note on learning problem with global perspectives
- Detecting Stochasticity in Discrete Signals via Nonparametric Excursion Theorem
- Manifold limit for the training of shallow graph convolutional neural networks
- A Generalized Adaptive Joint Learning Framework for High-Dimensional Time-Varying Models
- Comparison of Maximum Likelihood Classification Before and After Applying Weierstrass Transform
- Stochastic Deep Learning: A Probabilistic Framework for Modeling Uncertainty in Structured Temporal Data
- Progressive Bayesian Confidence Architectures for Cold-Start Personal Health Analytics: Formalizing Early Insight Through Posterior Contraction and Risk-Aware Interpretation
- A novel finite-sample testing procedure for composite null hypotheses via pointwise rejection
- Beyond Demand Estimation: Consumer Surplus Evaluation via Cumulative Propensity Weights
- A Modified Bayesian Criterion for Model Selection in Mixed and Hierarchical Frameworks
- Order-Constrained Spectral Causality for Multivariate Time Series
- A Novel Multiple Imputation Approach For Parameter Estimation in Observation-Driven Time Series Models With Missing Data
- Unmixing highly mixed grain size distribution data via maximum volume constrained end member analysis
- An exact unbiased semi-parametric L2 quasi-likelihood framework, complete in the presence of ties
- Deep learning estimation of the spectral density of functional time series on large domains