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Every paper Pith has read. Search by title, abstract, or pith.
1953 papers in stat · page 2
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Clinical AI models passing accuracy tests can fail hidden deployment checks
RISED: A Pre-Deployment Safety Evaluation Framework for Clinical AI Decision-Support Systems
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The paper develops a penalized optimization method that jointly detects change points and…
Change-point detection in variance-covariance matrix
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IV estimand equals new DATE under stochastic potential outcomes
Never Too LATE: A Fully Stochastic Update to the Potential Outcome Framework
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Array-RQMC cuts walk-on-spheres variance by up to 2290 times
Walk on spheres and Array-RQMC
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Digital twins build synthetic controls for single-arm trials
Digital Twins as Synthetic Controls in Single-Arm Trials
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Fusion penalty groups non-adjacent regions by income-COPD links
Linking COPD Prevalence with Income Distribution: A Spatial Heterogeneous Compositional Regression via Geographically Weighted Penalized Approach
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Adaptive multi-marginal couplings cut MCMC meeting times by half
Multi-Marginal Couplings for Metropolis-Hastings
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Outcome delays inflate sample sizes in re-estimation trials
Evaluating the impact of outcome delay on the efficiency of sample size re-estimation
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Bias from thresholding predicted by residual score variance
When to Trust Confidence Thresholding: Calibration Diagnostics for Pseudo-Labelled Regression
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Supply chain digital twin tests foundation models on logistics data
ISOMORPH: A Supply Chain Digital Twin for Simulation, Dataset Generation, and Forecasting Benchmarks
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Neural SDE cuts yield curve forecast error to 6.58 bps
Yield Curves Dynamics Using Variational Autoencoders Under No-arbitrage
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Longer blocks reduce efficiency in block maxima models
How long should a block be?
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Symmetries in token targets force circulant logit matrices in LLMs
Uncovering Symmetry Transfer in Large Language Models via Layer-Peeled Optimization
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Task structures and latents identifiable without supervision
From Generalist to Specialist Representation
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Optimal tests aggregate into log-optimal e-processes
Optimal sequential tests yield log-optimal e-processes
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Gap counting sets critical scale for attention softmax
A Unified Framework for Critical Scaling of Inverse Temperature in Self-Attention
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ABC and Gini scores risk dishonest model rankings for point predictions
Measures of predictive accuracy, miscalibration and discrimination
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Online optimization produces nested conformal sets at all levels
Online Conformal Prediction: Enforcing monotonicity via Online Optimization
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Inference-time optimization lifts RL trading returns without retraining
Plan Before You Trade: Inference-Time Optimization for RL Trading Agents
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KANs gain first risk bounds for mini-batch DP-SGD with correlated noise
Population Risk Bounds for Kolmogorov-Arnold Networks Trained by DP-SGD with Correlated Noise
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Orthogonal transformations keep weight singular values fixed
Pion: A Spectrum-Preserving Optimizer via Orthogonal Equivalence Transformation
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Sampler matches smooth-case rate for composite log-concave densities
A proximal gradient algorithm for composite log-concave sampling
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Bootstrap yields valid CIs for offline RL value functions
Model-based Bootstrap of Controlled Markov Chains
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Conformal prediction optimizes sets without data splits
Multi-Variable Conformal Prediction: Optimizing Prediction Sets without Data Splitting
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Online deferral algorithm manages varying experts with sublinear regret
Online Learning-to-Defer with Varying Experts
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Entropy-maximizing resampling mixes across disconnected manifolds
Manifold Sampling via Entropy Maximization
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Monotone operators approximated via graph convergence
Approximation of Maximally Monotone Operators : A Graph Convergence Perspective
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Pattern tests for independence get explicit null limits
Efficiency of pattern-based independence test
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Surrogates estimate time-dependent failure probabilities efficiently
Time-variant reliability using time-dependent surrogate models
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Budget-coverage policy learning reduces to affine threshold rule
Optimal Policy Learning under Budget and Coverage Constraints
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Self-predicted data calibrates Bayesian regression better than Laplace
Self-Supervised Laplace Approximation for Bayesian Uncertainty Quantification
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Sequential CMI bounds adaptive generalization gaps
Information-Theoretic Generalization Bounds for Sequential Decision Making
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Mixed-frequency synthetic controls reach optimal prediction error
Synthetic Control Method with Mixed Frequency Data
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Score gradients cut simulation needs for neural surrogates
Keeping Score: Efficiency Improvements in Neural Likelihood Surrogate Training via Score-Augmented Loss Functions
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Prior evidence boosts power in sequential multiple testing
Informative Simultaneous Confidence Intervals for Graphical Group Sequential Test Procedures
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Closed-form distributions on flat torus model protein torsions
Circula-based multivariate distributions on the flat torus, with applications in structural biology
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Bayesian model links realized volatility to prices for better forecasts
Bayesian Dynamic Modeling of Realized Volatility in Financial Asset Price Forecasting
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Laplacian-P-splines yield fast Gamma frailty fits for clustered survival
Laplacian-P-splines for shared Gamma frailty models applied to clustered right-censored time-to-event data
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No single test dominates power across multivariate problems
Power Studies For Two-Sample and Goodness-of-Fit Methods For Multivariate Data
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Laplacian neural operators learn PDE maps with polynomial cost
Approximation Theory of Laplacian-Based Neural Operators for Reaction-Diffusion System
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GNNs output random sets over classes to quantify epistemic uncertainty
Random-Set Graph Neural Networks
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Anchor quantization stabilizes Schrödinger bridge couplings
QDSB: Quantized Diffusion Schr\"odinger Bridges
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Weaker likelihood ratio shapes still give stochastic orders
Stochastic Ordering under Weaker Likelihood-Ratio Shape Conditions
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Bayesian mixture clusters mixed health outcomes with low-rank regressions
Bayesian low-rank latent-cluster regression for mixed health outcomes
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Ensemble models forecast daily tree water use from weather data
An ensemble prediction method for forecasting sap flux density and water-use in temperate trees
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Random sphere points give strong quantization for moderate n
Non-asymptotic quantisation of spherically symmetric distributions
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LOFT improves orthogonal fine-tuning via task-aware support selection
LOFT: Low-Rank Orthogonal Fine-Tuning via Task-Aware Support Selection
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Two anchors make reward variance identifiable from preferences
Variance-aware Reward Modeling with Anchor Guidance
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Kernel eigenvalue decay determines random forest rates
Minimax Rates and Spectral Distillation for Tree Ensembles