Model-Based Bootstrap

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3 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Calibrated Derivative-Process Sensitivity for Gaussian-Process Variable Selection
Sep 27, 2026Jia CaiGaussian Process False Discovery Rate
Department of Statistics, George Mason University Fairfax, Virginia, USA
How Reproducible Are Evaluation Conclusions? A Self-Audit of LLM-Inferred Prompt Structure
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Skelf Research
Model-based Bootstrap for Offline Policy Evaluation in Tabular Reinforcement Learning
Sep 17, 2026Weiwei Wang, Yuqiang Li, Xianyi Wu +1Model-Based Reinforcement Learning Model-Based Bootstrap
Department of Statistics and Data Science, Southern University of Science and Technology · School of Statistics & KLATASDS-MOE, East China Normal University · School of Artificial Intelligence, The Chinese University of Hong Kong, Shenzhen +1
Bagging Robustly Learns VC Classes with Linear Sample Complexity
Aug 13, 2026Omar MontasserEmpirical Risk Minimization Tree Ensembles
Yale University
Scale-to-Dialogue: Low-Burden Elicitation of Daily Premenstrual Symptom Ratings with Small Language Models
Aug 9, 2026Yifan WangElicitation Patients
The Chinese University of Hong Kong, Shenzhen (CUHK-Shenzhen)
Dirichlet Follow-the-Leader Closes the Gap in Simultaneous Multiclass U-Calibration
Aug 7, 2026Pahan DewasurendraModel-Based Bootstrap Optimistic Follow-The-Regularized-Leader
Johns Hopkins University
Nonparametric Goodness-of-fit Testing under Covariate Shift
Aug 5, 2026Zhen Hou, Dong XiaCovariate Shift Exponential Family
Department of Mathematics Hong Kong University of Science and Technology
Topological Simplification in Predictive Coding Networks
Aug 3, 2026Adam Shaw, Jiayu Li, Michael Sperling +2Predictive Coding Compressed Model
University of Southern California 3551 Trousdale Parkway, Los Angeles, CA 90089
Private Generative Bootstrap via Blocking
Aug 3, 2026Jinwon Sohn, Veronika RočkováModel-Based Bootstrap Bayesian
Booth School of Business, University of Chicago
Universal BCI Personalization: One API for Frozen EEG Trunks and Foundation Models
Jul 24, 2026Sergey MusienkoElectroencephalography Foundation Models Brain-Computer Interface
Prospective clinical indication, post-hoc report leakage, and fusion design in multi-image chest radiograph classification: a patient-clustered evaluation
Jul 15, 2026Kamran Shahid, Muhammad Munwar IqbalChest X-Ray Visible Image Fusion
Department of Computer Science, University of Engineering and Technology, Taxila, Pakistan
tsbootstrap: Distribution-Free Uncertainty Quantification and Conformal Prediction for Time Series
Jul 7, 2026Sankalp GildaModel-Based Bootstrap Time Series
DeepThought Solutions
Estimating Uncertainty in Classifier Performance with Applications to Large Language Models and Nested Data
Jun 24, 2026Kylie AnglinConfidence Intervals Large Language Model Classification
Department of Educational Psychology, Neag School of Education, University of Connecticut
Data augmented bootstrap: Unifying confidence interval construction by approximate invariance
Jun 8, 2026Kevin Han HuangModel-Based Bootstrap Confidence Intervals
Department of Statistics, University of Warwick
Shield-Loco: Shielding Locomotion Policies with Predictive Safety Filtering
Jun 5, 2026Aditya Shirwatkar, Sebastian Sanokowski, Shishir Kolathaya +2Safety Filters Agile Locomotion
Robert Bosch Center for Cyber Physical Systems, Indian Institute of Science, Bangalore, India · Munich Institute of Robotics and Machine Intelligence (MIRMI), Technical University of Munich, Munich, Germany · Department of Computer Science & Automation, Indian Institute of Science, Bangalore, India +2
Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series
May 28, 2026Hanyang Jiang, Rina Foygel Barber, Ashwin Pananjady +1Online Conformal Prediction Model-Based Bootstrap
Schools of Industrial and Systems Engineering⋆and Electrical and Computer Engineering†, Georgia Tech · Department of Statistics, University of Chicago‡
GeoFaith: A Spatio-Temporal Dual View of Faithful Chain-of-Thought
May 26, 2026Weijiang Lv, Wentong Zhao, Jiayu Wang +3Explanation Faithfulness Chain-of-Thought Reasoning
1Xidian University · 2Xi’an Jiaotong University · 3Mohamed bin Zayed University of Artificial Intelligence +2
When Do LLM Agents Treat Surface Noise Differently from Semantic Noise? A 68-Cell Measurement Study with a Held-Out Trace-Level Validation
May 25, 2026Liyun Zhang, Jiayi GuoLarge Language Model Agents Chain-of-Thought Reasoning
School of Information and Software Engineering, UESTC · Jacobs School of Engineering, UC San Diego
Collocational bootstrapping: A hypothesis about the learning of subject-verb agreement in humans and neural networks
May 19, 2026Claire Hobbs, R. Thomas McCoyLanguage Acquisition Syntactic Structure
Cognitive Science Program Yale University · Dept. of Linguistics & Wu Tsai Institute Yale University
Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation
May 19, 2026Ilya Levin, Maksim Shuklin, Eric Moulines +2Stochastic Approximation Model-Based Bootstrap
1HSE University, Russia · 2MBZUAI · 3CMAP, CNRS, École Polytechnique, Institut Polytechnique de Paris, 91120 Palaiseau, France
RoSHAP: A Distributional Framework and Robust Metric for Stable Feature Attribution
May 14, 2026Lanxin Xiang, Liang Shi, Youhui Ye +3Shapley Additive Explanations Model-Based Bootstrap
Department of Statistics Virginia Tech · Department of Statistics Virginia Tech Transportation Institute · Department of Computer Science Virginia Tech
Reducing cross-sample prediction churn in scientific machine learning
May 13, 2026Gordan Prastalo, Kevin Maik JablonkaChurn Prediction Model-Based Bootstrap
Helmholtz-Zentrum Berlin für Materialien und Energie GmbH, Hahn-Meitner-Platz 1, 14109 Berlin, Germany · HIPOLE Jena (Helmholtz Institute for Polymers in Energy Applications Jena), Lessingstrasse 12–14, 077432026 Jena, Germany · Laboratory of Organic and Macromolecular Chemistry (IOMC), Friedrich Schiller University Jena, Humboldtstrasse 10, 07743 Jena, Germany +2
Model-based Bootstrap of Controlled Markov Chains
May 12, 2026Ziwei Su, Imon Banerjee, Diego KlabjanModel-Based Reinforcement Learning Model-Based Bootstrap
Department of Industrial Engineering and Management Sciences Northwestern University Evanston, IL 60208
Sword: Style-Robust World Models as Simulators via Dynamic Latent Bootstrapping for VLA Policy Post-Training
May 8, 2026Jiaxuan Gao, Yongjian Guo, Zhong Guan +5World Models Reinforcement Learning Post-Training
Tianjin University · Tsinghua University · Swinburne University of Technology +1
DualSplat: Robust 3D Gaussian Splatting via Pseudo-Mask Bootstrapping from Reconstruction Failures
Apr 23, 2026Xu Wang, Zhiru Wang, Shiyun Xie +2Recent 3D Gaussian Splatting 3D Gaussian
1Beihang University · 2Peking University
Improving reproducibility by controlling random seed stability in machine learning based estimation via bagging
Apr 20, 2026Nicholas Williams, Alejandro SchulerModel-Based Bootstrap Random
Division of Biostatistics, University of California, Berkeley, California, U.S.A.
Forecasting Generative Amplification
Sep 9, 2025Henning Bahl, Sascha Diefenbacher, Nina Elmer +2Monte Carlo Model-Based Bootstrap
Institut für Theoretische Physik, Universität Heidelberg, Germany · Physics Division, Lawrence Berkeley National Laboratory, Berkeley, USA · Interdisciplinary Center for Scientific Computing (IWR), Universität Heidelberg, Germany
SaFeR-Steer: Evolving Multi-Turn MLLMs via Synthetic Bootstrapping and Feedback Dynamics
Date pendingHaolong Hu, Hanyu Li, Tiancheng He +6Mllm-Based Large Language Model Alignment
Huazhong University of Science and Technology · Beijing University of Posts and Telecommunications · West China Biomedical Big Data Center, Sichuan University +2
When Minute-Resolution Monitoring Meets Session-Level Injury Labels: Landmark-Based Discrimination in Elite Women's Football
Date pendingEvangelos Chatzidimitriou, Konstantinos TserpesAthleticism Physical Activities
National Technical University of Athens, Athens, Greece

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Calibrated Derivative-Process Sensitivity for Gaussian-Process Variable Selection

Jia Cai

Department of Statistics, George Mason University Fairfax, Virginia, USA

Gaussian Process False Discovery Rate Model Selection Model-Based Bootstrap

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Automatic relevance determination (ARD), the default tool for variable selection in Gaussian-process (GP) regression, ranks inputs by inverse lengthscales -- which measure how fast a function varies, not how much an input contributes to prediction -- and offers no calibrated rule for deciding which inputs to keep. The prediction-centred alternative, the derivative sensitivity

ν_j = \mathbb{E}[(\partial f/\partial x_j)^2]

, is available in closed form from a fitted GP, but turning it into a selection rule is harder than it looks: at a null input the estimator is a degenerate quadratic form, so Wald and Bernstein-von Mises cutoffs are anti-conservative, and the natural residual bootstrap is mis-scaled. We show that a studentized multiplier bootstrap of the GP derivative process repairs both, prove its validity through an invariance principle for quadratic forms, and obtain asymptotic family-wise and false-discovery-rate control across inputs. Over 100 replications the rule controls FDR wherever inputs are truly null, while uncalibrated derivative rankings breach the target by up to 2x and a Bernstein-von Mises cutoff by 2.2x; at matched FDR it loses no power; it holds under a Matérn kernel and input correlation up to 0.99; on real data with planted and authentic null inputs it admits 5-12x fewer spurious inputs; it costs 5-18% of the GP fit; and a block-averaged variant retains validity at cost linear in

n

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