arXiv Statistics @arxiv_stats@qoto.org

Object detection under the linear subspace model with application to cryo-EM images https://arxiv.org/abs/2405.00364 #math.ST #math.PR #stat.TH

Variational Bayesian Methods for a Tree-Structured Stick-Breaking Process Mixture of Gaussians https://arxiv.org/abs/2405.00385 #stat.ML #math.IT #cs.IT #cs.LG

Posterior exploration for computationally intensive forward models https://arxiv.org/abs/2405.00397 #stat.CO

Geometric Insights into Focal Loss: Reducing Curvature for Enhanced Model Calibration https://arxiv.org/abs/2405.00442 #stat.ML #cs.AI #cs.LG

Fast Adaptive Fourier Integration for Spectral Densities of Gaussian Processes https://arxiv.org/abs/2404.19053 #stat.CO #math.NA #cs.NA

Learning Sparse High-Dimensional Matrix-Valued Graphical Models From Dependent Data https://arxiv.org/abs/2404.19073 #stat.ML #eess.SP #cs.LG

Identification and estimation of causal effects using non-concurrent controls in platform trials https://arxiv.org/abs/2404.19118 #stat.ME

A model-free subdata selection method for classification https://arxiv.org/abs/2404.19127 #stat.ME #stat.ML

Orthogonal Bootstrap: Efficient Simulation of Input Uncertainty https://arxiv.org/abs/2404.19145 #stat.ME #econ.EM #math.ST #stat.ML #stat.TH #cs.LG

Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks https://arxiv.org/abs/2404.19157 #stat.ML #cs.LG

Detecting Spectral Breaks in Spiked Covariance Models https://arxiv.org/abs/2404.19176 #math.ST #stat.TH

Tail Asymptotic of Heavy-Tail Risks with Elliptical Copula https://arxiv.org/abs/2404.19196 #math.ST #math.PR #stat.TH

Regression for matrix-valued data via Kronecker products factorization https://arxiv.org/abs/2404.19220 #stat.ML #cs.LG

Variational approximations of possibilistic inferential models https://arxiv.org/abs/2404.19224 #stat.CO #stat.ME

A Bayesian Regression Approach for Estimating the Impact of COVID-19 on Consumer Behavior in the Restaurant Industry https://arxiv.org/abs/2404.08670 #stat.AP #stat.ML #cs.LG

Differentially Private Log-Location-Scale Regression Using Functional Mechanism https://arxiv.org/abs/2404.08715 #stat.ML #stat.AP #cs.CR #cs.LG

State-Space Systems as Dynamic Generative Models https://arxiv.org/abs/2404.08717 #stat.ML #math.DS #math.PR #math.ST #stat.TH #cs.LG

Seasonal and Periodic Patterns of PM2.5 in Manhattan using the Variable Bandpass Periodic Block Bootstrap https://arxiv.org/abs/2404.08738 #stat.AP #stat.OT

Observation-specific explanations through scattered data approximation https://arxiv.org/abs/2404.08747 #stat.ML #math.NA #cs.AI #cs.LG #cs.NA

Convergence of coordinate ascent variational inference for log-concave measures via optimal transport https://arxiv.org/abs/2404.08792 #stat.ML #math.OC #math.PR #math.ST #stat.TH #cs.LG