Probability & Statistics · Mathematics & Statistics
Applications
The newest papers in Applications that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
143 papers, from 4 September 2026 to 5 November 2026: 143 arXiv preprints.
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Newest papers
Adversarial Multiplicity: Cherry-Picked Models and the Limits of Disclosure
Predictive multiplicity -- where similarly accurate models disagree on individual predictions -- can be leveraged to optimize secondary metrics (e.g., fairness) without loss in predictive performance.Joint Modeling of Conditional Mean and Variability in Multilevel Functional Data: Application to Postprandial Glucose Trajectories in the AEGIS Study
Functional data analysis provides a framework for studying time-varying associations between covariates and high-frequency biological signals.The Gold Rush in AI4Math, II: What are signatures of AI-assisted Proofs?
The growing use of AI in mathematics raises a question: can we detect AI involvement in proofs, separately from AI assistance with writing?Does Your Trial Simulator Know What the Drug Does? An Intervention-Blind Test of Interventional Validity on 7,207 Registered Trials
Patient world models are increasingly proposed as simulators of clinical trials, and recent surveys rank their capabilities on a ladder from temporal prediction to counterfactual rollouts.Exponential Seniority Weighting Chain-Ladder Reserving
We develop a tractable state-space version of the chain-ladder model.An Interaction-Aware Decision Framework for FDIC-Assisted Distressed Bank Acquisitions: Empirical Evidence from the FDIC Failed-Bank Panel and the SVB-First Citizens Case
Acquirers of failed banks weigh acquisition value, regulatory protection, risk, buyer strength, and execution difficulty jointly, because each signal's meaning depends on the others: high…Integrating Machine Learning and Uncertainty Quantification for Real-Time Decision-Making in Digital Twins: A System-Centric Review and Perspective
Digital Twins are evolving from passive virtual representations into closed-loop systems that continuously synchronize with physical assets and drive real-time decisions.Hybrid Federated Learning for Multimodal Fusion under Missing Modalities and Site Heterogeneity
Multimodal fusion is studied under hybrid federation, where data are partitioned across samples and feature blocks.Reducing SNAP Payment Errors at Lower Cost With AI: A Simulation Study
New federal legislation will require states with high payment error rates in the Supplemental Nutrition Assistance Program (SNAP) to pay a share of benefit costs, potentially costing some states…RATSIFT: Resolution-Adaptive Transformer for Solar Irradiance Forecasting and Temporal Downscaling
Accurate forecasting and temporal downscaling of solar irradiance is critical for reliable renewable energy integration and grid management.Accuracy Is Not Risk: Why Medical AI Should Not Report Only Its Most Likely Label
Many medical AI models are trained to reproduce a single reference label and hand the most likely label to the next step in a clinical workflow.Sentiment sensing: comparative analysis of multilingual sentiment dynamics
Cross-country sentiment analysis faces three fundamental challenges: language-specific biases distort comparisons, compositional data constraints invalidate standard statistics and temporal dynamics…From fleet trajectories to single-cell promises: hierarchically weighted conformal prediction for battery SOH monitoring
Interval predictions from conformal prediction are usually read as "90% coverage", but on nested battery data that number promises the fleet average, not the individual cell.Transformer-Based Reinforcement Learning for Phase I Dose Allocation
Phase I dose-finding trials must learn from sparse toxicity observations while limiting exposure to overly toxic doses.Conformal Annotation with Randomized Expert Review: Application to Online Cell-Type Labeling
Artificial intelligence (AI) models can accelerate cell-type annotation in digital pathology, but safely scaling their use requires determining, with error control, which model-generated labels can…Model-Agnostic Search for New Physics in the Presence of Imperfect Background by Smearing the Data
In the search for new particles in high-energy physics, it is necessary to first define the signal region (SR) enriched in signal events, and then compare events in this region with the expected…FACTS-MAS: A Multi-Agent Architecture for Adaptive Forecasting from Heterogeneous Evidence
Real-world forecasting often requires integrating heterogeneous evidence whose predictive value varies across horizons, operating regimes, and domains.Modular Bayesian Foundation Models: Bayesian time series encoders for OOD detection, routing and forecasting
Industrial systems continuously generate time series that vary in sampling frequency, scale, dynamics, and operating regime.Balanced State Subspaces for Mamba-2 State Compression
Mamba-2 compresses all context into a fixed-size recurrent state that dominates decoding memory and bandwidth.The uneven rise of AI-generated web content
In less than five years, generative artificial intelligence (AI) has dramatically reshaped the public-facing web.