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1,205 records
- Calibrating the Brody exponent as a quantitative measure of short-range exclusion in 2D spatial point processes
- Statistical Foundations of LLM-based A/B Testing: A Surrogacy Framework for Human Causal Inference
- Bayesian Poisson-Randomized Gamma Tensor Factorization with Application to International Trade Flows
- Dependent Censoring Based on Geometric Optimization
- Tight $L_\infty$ Sample Complexity for Low-Degree and Sparse Boolean Polynomials
- Phase Transition in Convex Relaxations for Graph Alignment
- Information Gap and Feasibility-Aware Inference in Binomial Logistic Mixtures
- Stochastic trace estimation with tensor train random vectors
- A Koopman-PINN Framework for Epidemic Models: Parameter Inference and Forecasting
- Tail representations for absolute, signed-power, inverse, and logarithmic moments
- HSCI: Neyman-Orthogonal Causal Inference under High-Dimensional Proportional Hazards
- Predictive Concordance for Parameter Optimisation and Mixture Synthesis
- Joint Nuclear and $\ell_1$ Regularization for Logistic Matrix Regression with Applications to Brain Imaging
- On the design distribution for predictive Bayesian regression
- Prediction-Powered Causal Inference by Automatic Debiased Machine Learning and Semi-Supervised Riesz Regression
- Switching Hamiltonian Monte Carlo for sampling from mixture distributions
- Majority-of-Three is Optimal
- From Persistence to Survival: Hypothesis Testing, Effect Sizes and Vectorisation for Topological Features
- $k$-Nearest Neighbors in Gromov--Wasserstein Space
- Minimum free energy randomized design to improve covariate balance
- Deterministic Denominator Design for Localized Tamed Stochastic Gradient Langevin Dynamics
- Range Penalization: Theoretical Insights with Applications in Federated Learning
- The Statistical Compass
- Annealed Entropic Allocation for Ranking and Selection
- Second-Order Least Squares as a Special Case of the Polynomial Maximization Method
- Multi-Armed Bandits with Arriving Arms: Sequential Screening, Dynamic Regret, and Sublinear Guarantees
- Data augmented bootstrap: Unifying confidence interval construction by approximate invariance
- Convergence Rates for Neural-Network Estimation with Current-Status Data
- Nonparametric undirected graphical model selection using diffusion models
- Bayesian Global Fréchet Regression via Weak Conditional Expectations
- Empirical Transfer Operators and Finite-Sample Change Detection for Noisy Expanding Interval Maps
- The Effect of Training Task Diversity on In-Context Learning through the Lens of Low-Dimensional Subspaces
- Stability beyond Bounded Differences: Sharp Generalization Bounds under Finite $L_p$ Moments
- When can a posterior predictive check identify the learning rate? Exact degeneracy in Gaussian models and implications for Generalised Bayesian Inerence
- Principal Component Analysis for Multivariate Extremes
- Community Detection on a Randomly Growing Network
- Transfer learning for causal forest
- MediEncoder: Nonlinear Representation Learning for High-Dimensional Causal Mediation Analysis
- Wasserstein Exponential Smoothing for Distributional Time Series Forecasting
- Designing Zero-Mean Feature Functions for Multimodal Distributions
- Effective Dimensionality as an Operator Invariant for Physics-Preserving Constraint Adaptation in Physics-Informed Neural Networks
- Two-Sample Hypothesis Testing for Subspace Equality in Network Data
- Robust Prediction Variance Estimation for Gaussian Process Regression Under Covariance Smoothness Misspecification
- Powerful Multivariate Sensitivity Analysis via Sample Splitting in an Observational Study of the Effects of Poverty on Cardiovascular Disease Risk Factors
- Beyond First-order Asymptotics in Sequential Mean Testing
- Bayesian learning for the stochastic shortest path problem
- Deterministic Envelopes for Tamed SGLD: Decoupling Stochastic Gradient Noise and Localizing Taming
- Delayed acceptance sampling with Hamiltonian proposal subchains for random field materials inference
- A Fast Screening Approach for High-dimensional Outcomes and High-dimensional Predictors
- Modeling Discrete Data with High-Order Vector Potts Models