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Every paper Pith has read. Search by title, abstract, or pith.
6894 papers in stat · page 2
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Decision loss augments energy score for cost-aware forecasts
Decision-Aware Training for Sample-Based Generative Models
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Separable graphs unify independence models in mixed graphs
Characterizing and Identifying Separable Graphical Models
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Refined assumption gives dichotomy counts for low-dimensional data
Function-Counting Theory for Low-Dimensional Data Structures
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Monotone transforms unify multitask learning for mixed outcomes
Deep Multitask Learning for Mixed-Type Outcomes with Shared Sparsity
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Baseline treatment identifies effects despite informative switching
An Instrumental Variable Approach to Account for Informative Treatment Switching in Real-world Evidence
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GGMNIRA quantifies node influence via KL after mean manipulations
Simulating Node Manipulations in Gaussian Graphical Models: The GGMNIRA Framework for Continuous and Ordinal Psychological Network Data
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Bayesian model clusters Venice micro-mobility users into eight profiles
Beyond the Flow: A Bayesian Latent Clustering Framework for Shared Micro-mobility Users in Venice
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Planted subgraph recovery threshold set by minimal max density
Recovery of Planted Subgraphs
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Surrogate variable enables explicit process noise modeling in Kalman filters
Hierarchical Variational Kalman Filtering
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Transfer learning yields consistent quantile regression estimators
Transfert learning and adaptive LASSO quantile
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Latent achievement enters self-efficacy regression via conditional copula
How does academic performance affect self-efficacy? Interpretable modelling through latent academic achievement
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Symmetric CAEs yield more accurate latent trajectories in PDE models
Convolutional Symmetric AutoEncoders: enhancing latent stability via differential geometry
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Approximating region contains full-conformal set in multi-task regression
Approximate full-conformal multi-task regression with reproducing kernels
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MCMC proposals achieve near dimension-independent variance
Optimal scaling of MCMC algorithms: exploiting the symmetry of the Metropolis-Hastings formula
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Active-GRPO raises average SRxSim to 0.1773 by updating references
Active-GRPO: Adaptive Imitation and Self-Improving Reasoning for Molecular Optimization
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A staged framework uses SEM then OLS then double machine learning to check which survey…
From Structural Equation Modelling to Double Machine Learning: Robustness Analysis for Survey-Based Research
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Prototype LMs match dense baselines while attributing data 500x faster
Prototype Language Models
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Linear transformers map context distributions to responses at dim-free rates
Ghost in the Kernel: In-Context Learning with Efficient Transformers via Domain Generalization
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Neural network recovers time-varying AR coefficients for forecasts
Neural Network-Based Estimation of Time-Dependent Parameters in AR(p) Processes
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Distributed estimator reaches two-phase minimax rates for unidentifiable prediction
Distributed Prediction under Heterogeneity with Unidentifiable Parameter
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Intervals achieve nominal coverage for risk difference in paired data
Confidence Intervals for the Risk Difference in Combined Unilateral and Bilateral Data Incorporating a Distribution-Based Approach
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Selective borrowing lets hybrid trials use external data safely
Robust Estimation and Inference with Selective Borrowing in Hybrid Controlled Trials: A Tutorial with SelectiveIntegrative and intFRT
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Reverse-martingale RNN matches forecast skill while warning of drought ahead of SPI-3
Coupling Precipitation Forecasting and Early Warning with Reverse-Martingale Recurrent Neural Networks
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Three-stage estimator consistent for hybrid Lévy switching SDEs
Ergodicity and High-Frequency Inference for Hybrid Switching L\'{e}vy-Driven Stochastic Differential Equations
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FNOs achieve polynomial sample complexity on dissipative PDE operators
From Spectral Methods to Sample Complexity Bounds for Fourier Neural Operators
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Economic variables predict suicide rates in western counties
Economic Disparities and Their Relationship to Destructive Health Behaviors in Five Western U.S. States
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Valid intervals for network densities survive group selection from data
Post-selection inference for network structure
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Causal models recover Airbnb guest price responses from booking data
Understanding Guest Preferences and Optimizing Two-sided Marketplaces: Airbnb as an Example
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Entropy regularization improves sparse recovery in federated learning
Entropy-Regularized Probabilistic Gates for Sparse Model Discovery in Scarce-Data Federated Learning
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Worst-case top-k norm of heavy-tailed averages bounded by constants
Worst-Case Maximal Inequalities for Heavy-tailed Random Vectors
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X-VAE replaces standard normal prior with data-derived Gaussian
eXact-Prior Variational Autoencoder (X-VAE): Learning Data-Adaptive Gaussian Mixture Priors for Latent Distributions
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CTMC-Krylov and QBD recursions compute waiting times in dynamic-priority queues
Waiting time analysis in a finite-capacity multi-server systems with dynamic priorities, dynamically evolving customer types, and abandonment
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Full token observation lowers sample needs for watermark proportion estimates
Sample Complexities of Estimating Gumbel--Max Watermark Proportions with and without Reduction to Pivotal Statistics
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Full data beats pivotal reduction for watermark proportion estimates
Sample Complexities of Estimating Gumbel--Max Watermark Proportions with and without Reduction to Pivotal Statistics
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Marginal separable effects summarize causal effects for everyone
Causal Inference for All: Marginal Estimands for Outcomes Truncated by Death
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GLM formulation unifies Laplace BNN predictive estimators
A Short Review of Estimators for the GLM predictive of Laplace Bayesian Neural Networks
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No constant learning rate guarantees monotone descent in adversarial least squares
Homogenization of $\ell_2$-Adversarial Training in High-Dimensions: Exact Dynamics under Stochastic Gradient Descent
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Estimator fixes normal measurement errors in quantile regression
Quantile regression with measurement errors
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Three RL methods for LLMs reduce to one standard-deviation dial
GRPO, Dr. GRPO, and DAPO Are Three Operations on One Number: The Group-Standard-Deviation Identity
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SVGD particles stay close to mean-field limit for all time
Uniform-in-time Propagation-of-Chaos for Stein Variational Gradient Descent
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StaLoP boosts panel forecasts using similarity in target-local states
Similarity-Based Prediction for Digital Twins: Panel Data, Theory, and Applications
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Moment estimator consistent and normal for dynamic graph models
Analysis of a maximum-entropy based estimator for dynamic random graph models
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Random reshuffling beats SGD for any reasonable stepsize
Random Reshuffling Dominates Stochastic Gradient Descent
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Projection yields consistent payment estimators from macro insurance data
Payment Process Estimation in Aggregated Insurance Models
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Joint spatial model shrinks variances in ACS small-area estimates
Scalable Joint Modeling of Dependent Multi-Type Survey Data for Small Area Estimation
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Signed gauges recover 91% of RMSNorm coordinates across fine-tunes
Signed-Permutation Coordinate Transport for RMSNorm Transformers
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Argo data produces OHC maps with correlated uncertainty
Locally stationary Argo ocean heat content estimates: Modeling, validation and uncertainty quantification
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Conformal p-values select treatment beneficiaries with FDR control
A Conformal Selection Framework for Individual Treatment Beneficiaries with Auxiliary External Data
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Graph geometry and dependence set empirical rates
Coupling and Maximal Inequalities for Graph-Dependent Empirical Processes