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Every paper Pith has read. Search by title, abstract, or pith.
1988 papers in stat · page 3
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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
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Augmented KRR separates linear and nonlinear parts
Adaptive Kernel Ridge Regression with Linear Structure: Sharp Oracle Inequalities and Minimax Optimality
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Counterfactual probability identifies root causes from data
Probability of Root Cause: A Counterfactual Definition and Its Identification
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Nontargeted HPV infections isolate vaccine direct immune effect
Using NonTargeted HPV Infections in Studies with Risk Compensation
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Local clr LIMA detects composition mark clusters better than global averages
Uncovering Local Heterogeneity: Local Summary Characteristics for Spatial Point Processes with Composition-Valued Marks
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W-Flow reaches 1.29 FID in one ImageNet generation step
One-Step Generative Modeling via Wasserstein Gradient Flows
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Partial sharing yields tighter intervals under Byzantine attacks
Partial Model Sharing Improves Byzantine Resilience in Federated Conformal Prediction
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Bayesian bootstrap recovers Efron method as special case
Bayesian and Empirical Bayesian Bootstrapping
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Sparse Bayesian KANs achieve near-minimax contraction
Posterior Contraction Rates for Sparse Kolmogorov-Arnold Networks in Anisotropic Besov Spaces
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MLP scales small-ensemble covariances to cut EnKF error
Machine Learning-Based Covariance Correction for Ensemble Kalman Filter with Limited Ensemble Size
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Active label queries cut U-statistic variance with fixed budget
Learning U-Statistics with Active Inference
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McDiarmid bound removes K-scaling barrier in streaming decision trees
MIST: Reliable Streaming Decision Trees for Online Class-Incremental Learning via McDiarmid Bound
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Corrected audits flag discrimination in every Illinois insurer
Fairness Testing for Algorithmic Pricing
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Noise-subspace estimator matches minimax rate for probabilistic PLS
Exact Stiefel Optimization for Probabilistic PLS: Closed-Form Updates, Error Bounds, and Calibrated Uncertainty
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Unified theory supplies non-asymptotic bounds on conditional conformal errors
A Unified Theory of Conditional Coverage in Conformal Prediction with Applications
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Composite function stabilizes training of binary-activation networks
A Composite Activation Function for Learning Stable Binary Representations
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Model-matched designs raise accuracy in plant selection trials
The design of selection experiments using a model-based approach
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Generative model preserves climate variable links at 50x resolution
Generative climate downscaling enables high-resolution compound risk assessment by preserving multivariate dependencies
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Graph independences sharpen causal effect bounds
Exploiting independence constraints for efficient estimation of bounds on causal effects in the presence of unmeasured confounding
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Post-ADC inference restores valid stats after adaptive sampling
Post-ADC Inference: Valid Inference After Active Data Collection
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Calibration algorithms adapt error bounds to unknown non-stationarity
Adaptive Calibration in Non-Stationary Environments
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Vector codebook cuts KV cache to 34x compression at 0.95 similarity
FibQuant: Universal Vector Quantization for Random-Access KV-Cache Compression
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Barrier smoothing yields O(K^{-2/3}) stationarity for constrained bilevel opt
A Barrier-Metric First-Order Method for Linearly Constrained Bilevel Optimization
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PPO reformulated to beat SAC in multi-task RL
TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing
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Copula fixes dependence parameter to identify ordinal causal effects
Causal inference with ordinal outcomes: copula-based identification, estimation and sensitivity analysis
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Adapter adds closed-form spatial covariance to frozen predictors
Spatial Adapter: Structured Spatial Decomposition and Closed-Form Covariance for Frozen Predictors
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Causal model recovers recourse effects from observational data
Causal Algorithmic Recourse: Foundations and Methods
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Gaussian limits for spectral statistics survive fourth-moment corrections
The Geometry of Spectral Fluctuations: On Near-Optimal Conditions for Universal Gaussian CLTs, with Statistical Applications
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Balanced designs give exact ANOVA estimators for dose-response precision
Statistical evaluation of measurement precision in linear dose-response relationships via interlaboratory studies
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Decompositions isolate bias pathways in generative models
Causal Bias Detection in Generative Artifical Intelligence
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Causal paths break down survival disparities over time
Causal Fairness for Survival Analysis
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Inferring temperature improves hyperbolic models of tree-like networks
Hyperbolic Latent Space Models for Network Embedding: Model Specification and Bayesian Inference
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Algorithm identifies ε-good subtrees without knowing ε
$\varepsilon$-Good Action Identification in Fixed-Budget Monte Carlo Tree Search
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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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One operator unifies all regression types via measure choice
Unified Operator Framework for Functional and Multivariate Regression
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Similarity subgroups unmask hidden performance gaps in external validation
Rethinking external validation for the target population: Capturing patient-level similarity with a generative model
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Deterministic residual update removes stochastic variance in ensemble filters
A Data-Consistent Approach to Ensemble Filtering
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Dual form computes influence functions from data size not parameters
Extending Kernel Trick to Influence Functions
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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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Stable barcodes track how dependency clusters evolve in dynamic Bayesian networks
A Stable Distance Persistence Homology for Dynamic Bayesian Network Clustering
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Prediction markets lag behind statistical models for flu and measles
Prediction Markets Underperform Simple Baselines For Infectious Disease Forecasting
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Thompson sampling learns unknown networks while optimizing treatments
Adaptive Policy Learning Under Unknown Network Interference
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Random spectra match Muon on GPT-2 training
Muon is Not That Special: Random or Inverted Spectra Work Just as Well
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Kernel makes rotated 3D anisotropy explicit in Gaussian processes
Interpretable Machine Learning for Spatial Science: A Lie-Algebraic Kernel for Rotationally Anisotropic Gaussian Processes