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Every paper Pith has read. Search by title, abstract, or pith.
377 papers in stat.CO · page 2
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Surrogates estimate time-dependent failure probabilities efficiently
Time-variant reliability using time-dependent surrogate models
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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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Bayesian mixture clusters mixed health outcomes with low-rank regressions
Bayesian low-rank latent-cluster regression for mixed health outcomes
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Coupled noises lift diversity in diffusion batches at zero added cost
Couple to Control: Joint Initial Noise Design in Diffusion Models
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The paper develops a polynomial-time algorithm using semidefinite programming relaxation…
Efficient Robust Constrained Signal Detection via Kolmogorov Width Approximations
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Predictive resampling yields exact Bayesian posteriors
Variational predictive resampling
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VPR with mean-field predictives matches exact posteriors
Variational predictive resampling
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Writer monads automate MCMC kernel composition
gemlib.mcmc: composable kernels for Metropolis-within-Gibbs sampling schemes
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MCMC reaches O(ε²) error for time-changed SDE parameters at O(ε^{-2} log²ε) cost
Parameter Estimation for Partially Observed Time-Changed SDEs
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Metropolis-Hastings steps fix discretization bias in diffusion correctors
Metropolis-Adjusted Diffusion Models
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Random forest surrogate cuts likelihood evaluations in phylogenetic SMC
Accelerating Bayesian Phylogenetic Inference via Delayed Acceptance Sequential Monte Carlo with Random Forest Surrogates
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Shared parametric value function scales RL measurement to large tasks
Reinforcement Learning Measurement Model
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GPU solver speeds up entropic optimal transport calculations
cuRegOT: A GPU-Accelerated Solver for Entropic-Regularized Optimal Transport
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RQMC in walk-on-spheres beats Monte Carlo variance rates
Randomized quasi-Monte Carlo for walk on spheres
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Rolling calibration window optimizes conformal coverage for time series
Rolling-Origin Conformal Prediction under Local Stationarity and Weak Dependence
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Sampling varied commonsense proofs improves AI judgment of likely truths
Abductive Reasoning with Probabilistic Commonsense
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Differentiable relaxation recovers latent partial orders from linear traces
A Differentiable Bayesian Relaxation for Latent Partial-Order Inference
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QUBO reformulation finds higher-quality splits for regression trees
QUBO-Based Calibration for Regression Trees
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Time-position preconditioner unifies mode coverage and local exploration
Time-Inhomogeneous Preconditioned Langevin Dynamics
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Pretrained transformer solves PU classification in one forward pass
In-Context Positive-Unlabeled Learning
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Metaverse framework proposed for immersive statistical education
Welcome to the Statverse: A Metaverse for Data Science
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Direct sampling replaces Metropolis for global scale in sparse regression
Spectral Collapsed Gibbs Sampler for Bayesian Sparse Regression
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Symmetry-aware nets learn non-stationary GP kernels scalably
Permutation-preserving Functions and Neural Vecchia Covariance Kernels
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Decomposing coefficients by graph nodes yields stable doubly sparse regression
Proximal Projection for Doubly Sparse Regularized Models
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High-dimensional statistics connects to optimization and random matrices
High-Dimensional Statistics: Reflections on Progress and Open Problems
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Diffusion on incidence matrices generates better hypergraphs
Hypergraph Generation via Structured Stochastic Diffusion
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Penalized KLIC curbs over-selection of complex GMM models in longitudinal data
Penalized KLIC Model Selection for the Generalized Method of Moments in Longitudinal Data with Time-Dependent Covariates
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HIMCE cuts imputation error and halves MICE runtime in high dimensions
HIMCE: High-dimensional multiple imputation via covariance-mode updating for neuroimaging and spatiotemporal blocks
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Neural network assigns climate probabilities across the Sahara
Probabilistic Classification and Uncertainty Quantification of Sahara Desert Climate Using Feedforward Neural Networks
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Power can fall when adding more permutations to Monte Carlo tests
More Permutations Do Not Always Increase Power: Non-monotonicity in Monte Carlo Permutation Tests
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Joint amortized VI improves Bayesian predictive accuracy
Amortized Variational Inference for Joint Posterior and Predictive Distributions in Bayesian Uncertainty Quantification
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Covariance decomposition scales multi-fidelity spatio-temporal GPs
A new framework for non-stationary spatio-temporal data fusion of multi-fidelity models
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Nonparametric Hawkes model tops prediction for clustered extremes
Bayesian Modelling of Nonstationary Extreme Values Using a Nonparametric Hawkes Process
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Bayesian recursions track if a process is currently in control
Sequential Bayesian Monitoring for Recoverable and Drifting Processes
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Kernel discrepancy defines intrinsic ESS for manifold MCMC
Intrinsic effective sample size for manifold-valued Markov chain Monte Carlo via kernel discrepancy
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AI agents rate psychiatric symptoms better than humans on tricky cases
ADAPTS: Agentic Decomposition for Automated Protocol-agnostic Tracking of Symptoms
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LLM agents rate depression interviews closer to experts than original raters
ADAPTS: Agentic Decomposition for Automated Protocol-agnostic Tracking of Symptoms
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Regularized McKean-Vlasov dynamics scales sampling to 64 CV dimensions
High-Dimensional Enhanced Sampling via Regularized Path-Dependent McKean--Vlasov Dynamics using Tensor Density Approximation
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PMM estimators outperform OLS for skewed or heavy-tailed errors
EstemPMM: Polynomial Maximization Method for Non-Gaussian Regression and Time Series in R
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Few linear contrasts recover exact GP conditionals
Fast and accurate conditioning for large-scale and online Gaussian process prediction problems
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Auditing tool finds 25% reasoning gaps in DTI models despite matched accuracy
ISAAC: Auditing Causal Reasoning in Deep Models for Drug-Target Interaction
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R package fits Dirichlet process models without custom MCMC code
dirichletprocess: An R Package for Fitting Complex Bayesian Nonparametric Models
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Uniform generators speed Pearson IV sampling for all shapes
The Pearson IV distribution: Random variate generation and applications
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Functional Liu estimator selects shrinkage by direct MSE minimization
Functional Liu Regression for Scalar-on-Functional Models in High-Dimensional Settings
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Parallel subset chains boost MCMC sampling for multimodal targets
Modular Markov chain Monte Carlo with application to multimodal sampling
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Discriminator lowers error in small-ensemble filters
Learning Discriminators for Resampling in the Ensemble Gaussian Mixture Filter through a Normalizing Flow Approach
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Self-consistent method reduces entropy bias in small samples
SENECA: Small-Sample Discrete Entropy Estimation via Self-Consistent Missing Mass
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Three streaming covariance algorithms match exactly in exact math
$2B$ or Not $2B$: A Tale of Three Algorithms for Streaming: Covariance Estimation after Welford and Chan-Golub-LeVeque
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Sequential GPs enable streaming inference in signal processing
Sequential Inference for Gaussian Processes: A Signal Processing Perspective