AI News

⚡ 10 minutes ago
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ProbRes: Volatility Learning for Probabilistic Time-Series Forecasting (arxiv.org)
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When Softmax Fails at the Top: Extreme Value Corrections for InfoNCE (arxiv.org)
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ERICA: Quantifying Replicability of Cluster Analysis (arxiv.org)
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Riemannian Stochastic Optimization for Sufficient Dimension Reduction (arxiv.org)
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Interpreting FCDNNs via RG on Exponential Family (arxiv.org)
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Out-of-Distribution generalization of quantile regression with heavy tailed inputs: an SVM approach (arxiv.org)
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Is Zero-Shot Super-Resolution Possible in Operator Learning? (arxiv.org)
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Parameter-Free and Group Conditional Online Conformal Prediction (arxiv.org)
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Spectra-Guided Neural Tucker Factorization (arxiv.org)
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Taming the Loss Landscape of PINNs with Noisy Feynman-Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds (arxiv.org)
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On Median of Incomplete U-Statistics (arxiv.org)
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Statistical Testing on Directed Graphs by Surrogate Data Generation (arxiv.org)
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Statistical Analysis of using the Shapley Value for Sensor Anomaly Localization with Accurate Classifiers (arxiv.org)
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Bandit Simulation for Average Reward Inference (arxiv.org)
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Efficient Synthetic Network Generation via Latent Embedding Reconstruction (arxiv.org)
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Practical and Optimal Algorithm for Linear Contextual Bandits with Rare Parameter Updates (arxiv.org)
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Reinforcement Learning for Optimal Experiment Design in Parameter Identification of Mechatronic Systems (arxiv.org)
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Efficient Approximation for Encoder--Decoder Neural Operators via Variation Spaces (arxiv.org)
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Distribution-free changepoint localization after sequential change detection (arxiv.org)
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On the Uncertainty Quantification Ability of Tabular Foundation Models (arxiv.org)
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Computation-Aware Kalman Filtering with Model Selection for Neural Dynamics (arxiv.org)
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Self-Regulating Annealing in Heavy-Tailed Diffusion Models (arxiv.org)
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Knowledge-Intensive Video Generation (arxiv.org)
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Provable Data Scaling Law for Meta Learning via Complexity Minimization (arxiv.org)
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Convex Distance Operator Transport: A Convex and Geometry-Preserving Formulation (arxiv.org)
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Bayesian meta-learning for modeling Alzheimer's disease progression (arxiv.org)
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Identifiable Markov Switching Models with Instantaneous Effects and Exponential Families (arxiv.org)
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ShaplEIG: Bayesian Experimental Design for Shapley Value Estimation (arxiv.org)
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Doing well with less! On Sampling Techniques for Empirical Pairwise Loss Estimation/Minimization (arxiv.org)
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Sharpness-Aware Hybrid Model Learning for Architecture-Agnostic Parameter Estimation (arxiv.org)
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Hoeffding Concept Bottleneck Models with Applications to Overhead Images (arxiv.org)
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Physics from Video: Identifiability of Time-Invariant Second-Order ODEs under Minimal Trajectory Conditions (arxiv.org)
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Agentic Transformers Provably Learn to Search via Reinforcement Learning (arxiv.org)
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InfoAtlas: A Foundation Model for Zero-Shot Statistical Dependence Estimate (arxiv.org)
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Dynamics and Representation Structure of Local Approximations to Gradient-Based Learning in Linear Recurrent Neural Networks (arxiv.org)
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Accurate Large-sample Uncertainty Quantification using Stochastic Gradient Markov Chain Monte Carlo (arxiv.org)
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Large-scale Uncertainty Quantification for Latent Variable Models Using Subsampling Markov Chain Monte Carlo (arxiv.org)
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Perturbative methods for non-parametric instrumental variable (arxiv.org)
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Cluster Analysis with Resampling for Validation and Exploration (CARVE) (arxiv.org)
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Exploiting weight-space symmetries for approximating curvature (arxiv.org)
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Benchmarking Recursive-Collapse Warning Claims Under Matched False-Positive Control (arxiv.org)
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Polar Depth for Potentially Heavy-Tailed Data (arxiv.org)
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Tree-Structured Parzen Estimator: Understanding Its Algorithm Components and Their Roles for Better Empirical Performance (arxiv.org)
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Empirical Likelihood with Generative AI (arxiv.org)
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Weighted Conformal Clustering (arxiv.org)
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On the Limits of LLM Adaptability: Impact of Model-Internalized Priors on Annotation Task Performance (arxiv.org)
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Exploiting Similarities in A/B Testing with Off-Policy Estimation (arxiv.org)
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Zamba2-VL Technical Report (arxiv.org)
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Toward accurate RUL and SoH estimation using reinforced graph-based physics-informed neural networks enhanced with dynamic weights (arxiv.org)
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ChurnNet: A Optimized Modern AI for Churn Prediction (arxiv.org)