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1,244 records
- Maximin Robust Bayesian Experimental Design
- Edgewise Envelopes Between Balanced Forman and Ollivier-Ricci Curvature
- Robust Sequential Tracking via Bounded Information Geometry and Non-Parametric Field Actions
- Measuring Extreme Tail Association
- The Continuous Rank Probability Score of a Generalized Beta-Prime Distribution and Some Special Cases
- Bayesian Modular Inference for Copula Models with Potentially Misspecified Marginals
- On the Unit Teissier Distribution: Properties, Estimation Procedures and Applications
- Regenerative Rejection Sampling
- Sampling through iterated approximation: Gradient-free and multi-fidelity Bayesian inference via transport
- Inference for function-on-function regression: central limit theorem and residual bootstrap
- Combining e-values using demi-supermartingales
- Surrogate-Assisted Estimation of Exposure-Time Effects in Stepped-Wedge Trials with Administratively Censored Outcomes
- A Python implementation of some geometric tools on Kendall 3D shape space for practical applications
- Partition-Based Functional Ridge Regression for High-Dimensional Data
- Deep regression learning from dependent observations with minimum error entropy principle
- Continuous-time modeling and bootstrap for Schnieper's reserving
- Outrigger local polynomial regression
- Finite-Sample Decision Instability in Threshold-Based Process Capability Approval
- Verifying Good Regulator Conditions for Hypergraph Observers: Natural Gradient Learning from Causal Invariance via Established Theorems
- Sampling on Discrete Spaces with Temporal Point Processes
- A Generative Sampler for distributions with possible discrete parameter based on Reversibility
- A Diffusion Analysis of Policy Gradient for Stochastic Bandits
- An operator-level ARCH Model
- Generative Adversarial Regression (GAR): Learning Conditional Risk Scenarios
- Dirichlet kernel density estimation on the simplex with missing data
- Probabilistic Inference and Learning with Stein's Method
- Evaluating consumption effects of intelligent control algorithms for district heated buildings
- Group-Sparse Smoothing for Longitudinal Models with Time-Varying Coefficients
- Fréchet regression of multivariate distributions with nonparanormal transport
- Integrating Heterogeneous Information in Randomized Experiments: A Unified Calibration Framework
- A note on diffusive/random-walk behaviour in Metropolis--Hastings algorithms
- Bayesian Linear Programming under Learned Uncertainty: Posterior Feasibility Guarantees, Scenario Certification, and Applications
- A Hierarchical Bayesian Dynamic Game for Competitive Inventory and Pricing under Incomplete Information: Learning, Credible Risk, and Equilibrium
- Robust estimation via $γ$-divergence for diffusion processes
- How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression?
- Bayes with No Shame: Admissibility Geometries of Predictive Inference
- On the Statistical Optimality of Optimal Decision Trees
- Thermodynamic Response Functions in Singular Bayesian Models
- Random Dot Product Graphs as Dynamical Systems: Limitations and Opportunities
- Empirical Evaluation of No Free Lunch Violations in Permutation-Based Optimization
- Riemannian Langevin Dynamics: Strong Convergence of Geometric Euler-Maruyama Scheme
- Generalization Properties of Score-matching Diffusion Models for Intrinsically Low-dimensional Data
- The projected isotropic normal distribution with applications in neuroscience
- Beyond Mixtures and Products for Ensemble Aggregation: A Likelihood Perspective on Generalized Means
- A spectral inference method for determining the number of communities in networks
- Bayesian Modeling of Collatz Stopping Times: A Probabilistic Machine Learning Perspective
- Combinatorial Sparse PCA Beyond the Spiked Identity Model
- A Covering Framework for Offline POMDPs Learning using Belief Space Metric
- Density-Matrix Spectral Embeddings for Categorical Data: Operator Structure and Stability
- Mini-Batch Covariance, Diffusion Limits, and Oracle Complexity in Stochastic Gradient Descent: A Sampling-Design Perspective