1,205 records
- Adaptive Subspace Modeling With Functional Tucker Decomposition
- Beyond identifiability: Learning causal representations with few environments and finite samples
- Context Tree Prior Distributions based on Node Weighting with exact Bayes Factors
- Design-Based Anytime-Valid Inference for Randomized Experiments with Delayed Outcomes and Staggered Entry
- Beyond Consistency: Inference for the Relative risk functional in Deep Nonparametric Cox Models
- Tackling the 6/49 Lottery and Debunking Common Myths with Probabilistic Methods and Combinatorial Designs
- XT-REM: A Two-Component Model for Meta-Analysis of Extreme Event Proportions
- Rethinking Individual Risk and Aggregation in Survival Analysis: A Latent Mechanism Framework
- E-values as statistical evidence: A comparison to Bayes factors, likelihoods, and p-values
- Improving online FDR procedures via online analogs of e-closure and compound e-values
- Interpretable Causal Graphical Models for Equilibrium Systems with Confounding
- High-Resolution Tensor-Network Fourier Methods for Exponentially Compressed Non-Gaussian Aggregate Distributions
- Kinetic Langevin Splitting Schemes for Constrained Sampling
- Dynamical behaviors of a stochastic SIS epidemic model with mean-reverting inhomogeneous geometric brownian motion
- Wasserstein Parallel Transport for Predicting the Dynamics of Statistical Systems
- Cost-Aware Optimized Front-Door Experimental Design
- Detecting change regions on spheres
- Generalized Sequential Monte Carlo Sampling for Redistricting Simulation
- SPDE Methods for Nonparametric Bayesian Posterior Contraction and Laplace Approximation
- Gradient Descent with Projection Finds Over-Parameterized Neural Networks for Learning Low-Degree Polynomials with Nearly Minimax Optimal Rate
- Stochastic approximation in non-markovian environments revisited
- Accelerate Vector Diffusion Maps by Landmarks
- Tiny but uniform improvements of adaptive BH procedures via compound e-values
- Sinkhorn Based Associative Memory Retrieval Using Spherical Hellinger Kantorovich Dynamics
- Continuity of the Solution of a Non-Parametric Bayesian Statistical Calibration Procedure
- Ordinal Patterns Based Testing of Spatial Independence in Irregular Spatial Structures
- Auto-differentiable data assimilation: Co-learning of states, dynamics, and filtering algorithms
- Weak-Form Recovery of Stochastic Generators
- Stability of Sequential and Parallel Coordinate Ascent Variational Inference
- Surrogate-Guided Adaptive Importance Sampling for Failure Probability Estimation
- Hard labels sampled from sparse targets mislead rotation invariant algorithms
- Graph-Informed Adversarial Modeling: Infimal Subadditivity of Interpolative Divergences
- Posterior inference via Hill's prediction model
- Measure flow path recovery in Bayes Hilbert spaces
- Operator Learning for Smoothing and Forecasting
- Goal-oriented learning of stochastic differential equations using error bounds on path-space observables
- Precise Performance of Linear Denoisers in the Proportional Regime
- A Theoretical Comparison of No-U-Turn Sampler Variants: Necessary and Sufficient Convergence Conditions and Mixing Time Analysis under Gaussian Targets
- Kernel Single-Index Bandits: Estimation, Inference, and Learning
- Pseudo-Labeling for Unsupervised Domain Adaptation with Kernel GLMs
- Regression Adjustments for Double Randomization in Two-Sided Marketplaces
- Empirical Likelihood Inference for Sen and Sen--Shorrocks--Thon Indices
- Mirror Descent on Riemannian Manifolds
- Prediction with Missing Data: Target Probabilities and Missingness Mechanisms
- Multi-Armed Sequential Hypothesis Testing by Betting
- On min-Storey estimators for multiple testing and conformal novelty detection
- ResNets of All Shapes and Sizes: Convergence of Training Dynamics in the Large-scale Limit
- Conditional Distributional Treatment Effects: Doubly Robust Estimation and Testing
- Refined Inference for Asymptotically Linear Estimators with Non-Negligible Second-Order Remainders
- Self-Regularized Learning Methods