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1,205 records
- Inference for Causal Path-Specific Effects in Longitudinal Studies with Repeated Treatments and Multiple Mediators
- Intrinsic Gradient Barriers in Pushforward Deep Generative Models
- Certifying Distributionally Robust Decisions from Projection Observations
- Demand Estimation with Unobserved Stockout Substitution: Exact Likelihood Maximization
- Recursive moment updates for scalable Bayesian nonparametric regression
- Online Covariance Estimation for Averaged Stochastic Gradient Descent on Riemannian Manifolds
- Affine-invariant Cubic Newton with Weak Learners
- On the Error Analysis of Triangular Transport Maps for Conditional Generation via MMD-based Objectives
- Identification and curvature bias for shared inputs in multichannel dynamical models
- Renewable model averaging for generalized linear models
- An Integrated Framework for Assessing Interpretability in Exploratory Factor Analysis
- Optimal Experimental Design for the Polynomial Maximization Method: a Higher-Order Reserve Beyond Second-Order Design Theory
- Higher Order Asymptotics of Regression Adjustment Estimators for Causal Inference
- Implicit Neural Representations for Variational Problems on Graphons
- Mapping Academic Sports Analytics: A Content Analysis of JQAS and JSA
- Exact Global Minimax Risk near Nonidentification
- Score-Preserving Continual Lasso under Task Shift
- Kernelised covariance matrices, dimension reduction and imbalanced spectral clustering
- Not All Mislabels Are Equal: Efficient Task-Aware Auditing with Confidence Sequences
- Sequential Monte Carlo Sampling of Feasible Regions Represented by R-Functions
- Deep Learning for Random Objects in Metric Spaces: Beyond Manifold Assumptions
- Dimension-free regimes for unadjusted Langevin in ridge-separable models: A subspace robust Wasserstein analysis
- Maximum Likelihood Estimation and Likelihood Ratio Tests for the Power Spherical Distribution
- Early learning in large residual networks
- Parallel Trends as a Spectrum
- A unified approach for estimation of unnormalized models via Stein operators
- Differentially Private Synthetic Data via Generalized Moment Matching
- Bridge change-of-measure for propagator estimation of diffusions
- Beyond exponential tilting: sharp asymptotics and improved importance sampling for rare events
- Geometry-informed importance sampling for rare events
- Annealed correlation and quenched noise sensitivity in biased deep neural networks
- Nonparametric In-Context Learning and Inference via Measure-Indexed Kernel Ridge Regression
- Likelihood-Based Confidence Curves for Bounded Parameters
- Confessions of a Masked MDP
- Borrowing Strength Across Stores: Transfer Learning for Choice-Based Revenue Management
- Anytime-Valid Inference in Linear Models with Clustered Outcomes: Exact Multivariate Tests and Cluster-Robust Confidence Sequences
- Corrected Block Sparse Spectral Optimization: Exact Models, Finite Identification, and Local Dynamics
- Gaussian Approximation of Besov Functions for Logistic Classification on Manifolds
- The Geometry of Informativeness: A Bregman-Centroid Diagnostic for Partial Pooling in Multisite Trials
- Information-Geometric Blind Spots of Conformal Test Martingales
- Testing Treatment Effect Heterogeneity with Functional Outcomes
- A general recipe for data-adaptive anytime-valid envelopes for iterative algorithms
- Parametric Resonance in Primal-Dual Learning for Slowly Non-Stationary Constrained MDPs
- PICKLES: Covariance-Preconditioned Kinetic Langevin Ensemble Sampler
- Pathwise Shrinkage and Probabilistic Calibration of the Multiplicative Half-Cauchy Process
- Reconstructing constant point heat sources from few temperature sensors: sparse selection and spatial resolution
- Dimension-Free PAC-Bayes Generalization for Deep Neural Networks via Dirichlet Processes
- A perturbation theory for Feynman-Kac models and their particle interpretations
- Optimal approximation of smooth functions by ReLU neural networks
- Negative-binomial ensemble filtering for discrete-time Hawkes network reconstruction