AI News

ProbRes: Volatility Learning for Probabilistic Time-Series Forecasting (arxiv.org)

When Softmax Fails at the Top: Extreme Value Corrections for InfoNCE (arxiv.org)

ERICA: Quantifying Replicability of Cluster Analysis (arxiv.org)

Riemannian Stochastic Optimization for Sufficient Dimension Reduction (arxiv.org)

Interpreting FCDNNs via RG on Exponential Family (arxiv.org)

Out-of-Distribution generalization of quantile regression with heavy tailed inputs: an SVM approach (arxiv.org)

Is Zero-Shot Super-Resolution Possible in Operator Learning? (arxiv.org)

Parameter-Free and Group Conditional Online Conformal Prediction (arxiv.org)

Spectra-Guided Neural Tucker Factorization (arxiv.org)

Taming the Loss Landscape of PINNs with Noisy Feynman-Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds (arxiv.org)

On Median of Incomplete U-Statistics (arxiv.org)

Statistical Testing on Directed Graphs by Surrogate Data Generation (arxiv.org)

Statistical Analysis of using the Shapley Value for Sensor Anomaly Localization with Accurate Classifiers (arxiv.org)

Bandit Simulation for Average Reward Inference (arxiv.org)

Efficient Synthetic Network Generation via Latent Embedding Reconstruction (arxiv.org)

Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates (arxiv.org)

Reinforcement Learning for Optimal Experiment Design in Parameter Identification of Mechatronic Systems (arxiv.org)

Efficient Approximation for Encoder--Decoder Neural Operators via Variation Spaces (arxiv.org)

Distribution-free changepoint localization after sequential change detection (arxiv.org)

On the Uncertainty Quantification Ability of Tabular Foundation Models (arxiv.org)

Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics (arxiv.org)

Self-Regulating Annealing in Heavy-Tailed Diffusion Models (arxiv.org)

Knowledge-Intensive Video Generation (arxiv.org)

Provable Data Scaling Law for Meta Learning via Complexity Minimization (arxiv.org)

Convex Distance Operator Transport: A Convex and Geometry-Preserving Formulation (arxiv.org)

Bayesian meta-learning for modeling Alzheimer's disease progression (arxiv.org)

Identifiable Markov Switching Models with Instantaneous Effects and Exponential Families (arxiv.org)

ShaplEIG: Bayesian Experimental Design for Shapley Value Estimation (arxiv.org)

Doing well with less! On Sampling Techniques for Empirical Pairwise Loss Estimation/Minimization (arxiv.org)

Sharpness-Aware Hybrid Model Learning for Architecture-Agnostic Parameter Estimation (arxiv.org)

Hoeffding Concept Bottleneck Models with Applications to Overhead Images (arxiv.org)

Physics from Video: Identifiability of Time-Invariant Second-Order ODEs under Minimal Trajectory Conditions (arxiv.org)

Agentic Transformers Provably Learn to Search via Reinforcement Learning (arxiv.org)

InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate (arxiv.org)

Dynamics and Representation Structure of Local Approximations to Gradient-Based Learning in Linear Recurrent Neural Networks (arxiv.org)

Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo (arxiv.org)

Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo (arxiv.org)

Perturbative methods for non-parametric instrumental variable (arxiv.org)

Cluster Analysis with Resampling for Validation and Exploration (CARVE) (arxiv.org)

Exploiting weight-space symmetries for approximating curvature (arxiv.org)

Benchmarking Recursive-Collapse Warning Claims Under Matched False-Positive Control (arxiv.org)

Polar Depth for Potentially Heavy-Tailed Data (arxiv.org)

Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance (arxiv.org)

Empirical Likelihood with Generative AI (arxiv.org)

Weighted Conformal Clustering (arxiv.org)

On the Limits of LLM Adaptability: Impact of Model-Internalized Priors on Annotation Task Performance (arxiv.org)

Exploiting Similarities in A/B Testing with Off-Policy Estimation (arxiv.org)

Zamba2-VL Technical Report (arxiv.org)

Toward accurate RUL and SoH estimation using reinforced graph-based physics-informed neural networks enhanced with dynamic weights (arxiv.org)

ChurnNet: A Optimized Modern AI for Churn Prediction (arxiv.org)