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- Integrating Machine Learning and Uncertainty Quantification for Real-Time Decision-Making in Digital Twins: A System-Centric Review and Perspective
- OmniST: Topology-Invariant Spatiotemporal Forecasting with Guaranteed-Coverage Uncertainty at Unseen Sensor Locations
- Aggregate Calibration Can Mask Stress-State Undercoverage: Bounded-Memory Forecast Intervals under Recurrent Financial Stress
- Deterministic Uniformization for Estimation and Latent Trajectory Inference in Interval-Censored Multistate Triansition Models
- Two-Layer Random ReLU Networks Can Separate Disjoint Classes
- Statistical Machine Learning for Medicinal Plant Leaves Classification
- Terrain-Surface-Area Cover from LiDAR: Inverse-Probability-Weighted Estimation and a Global Cramér-von Mises Lack-of-Fit Test
- Few-Step Boltzmann Generators via Scalable Likelihood Flow Maps
- Modified treatment policies that depend on the sequence of natural treatment values
- Missing data and cluster graphs: cluster-level missingness vs variable-level missingness
- TabPFN-3: Technical Report
- TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing
- Sink vs. diagonal patterns as mechanisms for attention switch and oversmoothing prevention
- A simple adaptive accelerated optimistic dual averaging method for unconstrained convex optimization in p-norm geometry
- Conformal Prediction at Performative Equilibrium: The Price of Performativity
- Logarithmic Regret for Alternating Mirror Descent
- Ensembles of Random Partition-Based Models under Covariate Shift
- A Random Matrix Analysis of Symmetric Tensor Unfolding
- Beyond Multi-Index Models: Learning Intersections of Degree-2 PTFs
- Enabling risk and reliability analysis in next-generation computational tools via multifidelity methods
- On the Onsager--Machlup functional of the infinite-dimensional angular central Gaussian distribution and related measures
- Approximating Distributions on Vertex Degrees in Random Hypergraphs via Stein's Method
- Decentralized Sparse Quantile Regression
- Estimating "Realized" Skewness using Convolutional Neural Network
- Nuisance structure and the detection boundary for population size: how profiling can change a rate, not only a constant