arXiv stat.ME Methodology
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Reposted by arXiv stat.ME Methodology
Abhik Ghosh, Suryasis Jana: Provably robust learning of regression neural networks using $\beta$-divergences https://arxiv.org/abs/2602.08933 https://arxiv.org/pdf/2602.08933 https://arxiv.org/html/2602.08933
February 10, 2026 at 6:53 AM
Abhik Ghosh, Suryasis Jana: Provably robust learning of regression neural networks using $\beta$-divergences https://arxiv.org/abs/2602.08933 https://arxiv.org/pdf/2602.08933 https://arxiv.org/html/2602.08933
Reposted by arXiv stat.ME Methodology
Rohan Hore, Ruodu Wang, Aaditya Ramdas: Online monotone density estimation and log-optimal calibration https://arxiv.org/abs/2602.08927 https://arxiv.org/pdf/2602.08927 https://arxiv.org/html/2602.08927
February 10, 2026 at 6:53 AM
Rohan Hore, Ruodu Wang, Aaditya Ramdas: Online monotone density estimation and log-optimal calibration https://arxiv.org/abs/2602.08927 https://arxiv.org/pdf/2602.08927 https://arxiv.org/html/2602.08927
Reposted by arXiv stat.ME Methodology
Xiaotong Liu, Shao-Bo Lin, Jun Fan, Ding-Xuan Zhou: Two-Stage Data Synthesization: A Statistics-Driven Restricted Trade-off between Privacy and Prediction https://arxiv.org/abs/2602.08657 https://arxiv.org/pdf/2602.08657 https://arxiv.org/html/2602.08657
February 10, 2026 at 6:36 AM
Xiaotong Liu, Shao-Bo Lin, Jun Fan, Ding-Xuan Zhou: Two-Stage Data Synthesization: A Statistics-Driven Restricted Trade-off between Privacy and Prediction https://arxiv.org/abs/2602.08657 https://arxiv.org/pdf/2602.08657 https://arxiv.org/html/2602.08657
Reposted by arXiv stat.ME Methodology
Yash Patel, Ambuj Tewari: Distribution-Free Robust Functional Predict-Then-Optimize https://arxiv.org/abs/2602.08215 https://arxiv.org/pdf/2602.08215 https://arxiv.org/html/2602.08215
February 10, 2026 at 6:35 AM
Yash Patel, Ambuj Tewari: Distribution-Free Robust Functional Predict-Then-Optimize https://arxiv.org/abs/2602.08215 https://arxiv.org/pdf/2602.08215 https://arxiv.org/html/2602.08215
Reposted by arXiv stat.ME Methodology
Cristian Minoccheri, Sophia Tesic, Kayvan Najarian, Ryan Stidham: A Causal Machine Learning Framework for Treatment Personalization in Clinical Trials: Application to Ulcerative Colitis https://arxiv.org/abs/2602.08171 https://arxiv.org/pdf/2602.08171 https://arxiv.org/html/2602.08171
February 10, 2026 at 6:35 AM
Cristian Minoccheri, Sophia Tesic, Kayvan Najarian, Ryan Stidham: A Causal Machine Learning Framework for Treatment Personalization in Clinical Trials: Application to Ulcerative Colitis https://arxiv.org/abs/2602.08171 https://arxiv.org/pdf/2602.08171 https://arxiv.org/html/2602.08171
Reposted by arXiv stat.ME Methodology
Tran, Nguyen, Bashar, Ho, Nayak, Drovandi: Fast Model Selection and Stable Optimization for Softmax-Gated Multinomial-Logistic Mixture of Experts Models https://arxiv.org/abs/2602.07997 https://arxiv.org/pdf/2602.07997 https://arxiv.org/html/2602.07997
February 10, 2026 at 6:53 AM
Tran, Nguyen, Bashar, Ho, Nayak, Drovandi: Fast Model Selection and Stable Optimization for Softmax-Gated Multinomial-Logistic Mixture of Experts Models https://arxiv.org/abs/2602.07997 https://arxiv.org/pdf/2602.07997 https://arxiv.org/html/2602.07997
Reposted by arXiv stat.ME Methodology
Kim, Parmar, Wallis, Miculicich, Jung, Dvijotham, Le, Pfister: CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution https://arxiv.org/abs/2602.07918 https://arxiv.org/pdf/2602.07918 https://arxiv.org/html/2602.07918
February 10, 2026 at 6:30 AM
Kim, Parmar, Wallis, Miculicich, Jung, Dvijotham, Le, Pfister: CausalArmor: Efficient Indirect Prompt Injection Guardrails via Causal Attribution https://arxiv.org/abs/2602.07918 https://arxiv.org/pdf/2602.07918 https://arxiv.org/html/2602.07918
Reposted by arXiv stat.ME Methodology
Huiyang Yi, Xiaojian Shen, Yonggang Wu, Duxin Chen, He Wang, Wenwu Yu: CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios https://arxiv.org/abs/2602.07915 https://arxiv.org/pdf/2602.07915 https://arxiv.org/html/2602.07915
February 10, 2026 at 6:34 AM
Huiyang Yi, Xiaojian Shen, Yonggang Wu, Duxin Chen, He Wang, Wenwu Yu: CausalCompass: Evaluating the Robustness of Time-Series Causal Discovery in Misspecified Scenarios https://arxiv.org/abs/2602.07915 https://arxiv.org/pdf/2602.07915 https://arxiv.org/html/2602.07915
Reposted by arXiv stat.ME Methodology
Yufei Zhang, Zhihao Ma: Digital exclusion among middle-aged and older adults in China: age-period-cohort evidence from three national surveys, 2011-2022 https://arxiv.org/abs/2602.07785 https://arxiv.org/pdf/2602.07785 https://arxiv.org/html/2602.07785
February 10, 2026 at 6:52 AM
Yufei Zhang, Zhihao Ma: Digital exclusion among middle-aged and older adults in China: age-period-cohort evidence from three national surveys, 2011-2022 https://arxiv.org/abs/2602.07785 https://arxiv.org/pdf/2602.07785 https://arxiv.org/html/2602.07785
Reposted by arXiv stat.ME Methodology
Ruizhe Deng, Bibhas Chakraborty, Ran Chen, Yan Shuo Tan: BFTS: Thompson Sampling with Bayesian Additive Regression Trees https://arxiv.org/abs/2602.07767 https://arxiv.org/pdf/2602.07767 https://arxiv.org/html/2602.07767
February 10, 2026 at 6:53 AM
Ruizhe Deng, Bibhas Chakraborty, Ran Chen, Yan Shuo Tan: BFTS: Thompson Sampling with Bayesian Additive Regression Trees https://arxiv.org/abs/2602.07767 https://arxiv.org/pdf/2602.07767 https://arxiv.org/html/2602.07767
Reposted by arXiv stat.ME Methodology
Trevor Harris: Flow-Based Conformal Predictive Distributions https://arxiv.org/abs/2602.07633 https://arxiv.org/pdf/2602.07633 https://arxiv.org/html/2602.07633
February 10, 2026 at 6:53 AM
Trevor Harris: Flow-Based Conformal Predictive Distributions https://arxiv.org/abs/2602.07633 https://arxiv.org/pdf/2602.07633 https://arxiv.org/html/2602.07633
Reposted by arXiv stat.ME Methodology
Wanru Guo, Juan Xie, Binbin Wang, Weicong Chen, Xiaoyi Lu, Vipin Chaudhary, Curtis Tatsuoka: Robust Ultra-High-Dimensional Variable Selection With Correlated Structure Using Group Testing https://arxiv.org/abs/2602.07258 https://arxiv.org/pdf/2602.07258 https://arxiv.org/html/2602.07258
February 10, 2026 at 6:33 AM
Wanru Guo, Juan Xie, Binbin Wang, Weicong Chen, Xiaoyi Lu, Vipin Chaudhary, Curtis Tatsuoka: Robust Ultra-High-Dimensional Variable Selection With Correlated Structure Using Group Testing https://arxiv.org/abs/2602.07258 https://arxiv.org/pdf/2602.07258 https://arxiv.org/html/2602.07258
Reposted by arXiv stat.ME Methodology
Matthew LeDuc, Tomoko Matsuo: PoissonRatioUQ: An R package for band ratio uncertainty quantification https://arxiv.org/abs/2602.07165 https://arxiv.org/pdf/2602.07165 https://arxiv.org/html/2602.07165
February 10, 2026 at 6:53 AM
Matthew LeDuc, Tomoko Matsuo: PoissonRatioUQ: An R package for band ratio uncertainty quantification https://arxiv.org/abs/2602.07165 https://arxiv.org/pdf/2602.07165 https://arxiv.org/html/2602.07165
Rishikesh Yadav, Arnab Hazra: Regression modeling of multivariate precipitation extremes under regular variation https://arxiv.org/abs/2602.08865 https://arxiv.org/pdf/2602.08865 https://arxiv.org/html/2602.08865
February 10, 2026 at 6:53 AM
Rishikesh Yadav, Arnab Hazra: Regression modeling of multivariate precipitation extremes under regular variation https://arxiv.org/abs/2602.08865 https://arxiv.org/pdf/2602.08865 https://arxiv.org/html/2602.08865
Yuta Kawakami, Jin Tian: Measures for Assessing Causal Effect Heterogeneity Unexplained by Covariates https://arxiv.org/abs/2602.08647 https://arxiv.org/pdf/2602.08647 https://arxiv.org/html/2602.08647
February 10, 2026 at 6:53 AM
Yuta Kawakami, Jin Tian: Measures for Assessing Causal Effect Heterogeneity Unexplained by Covariates https://arxiv.org/abs/2602.08647 https://arxiv.org/pdf/2602.08647 https://arxiv.org/html/2602.08647
Max Rubinstein, Megan S. Schuler, Elizabeth A. Stuart, Bradley D. Stein, Max Griswold, Elizabeth M. Stone, Beth Ann Griffin: State policy heterogeneity analyses: considerations and proposals https://arxiv.org/abs/2602.08643 https://arxiv.org/pdf/2602.08643 https://arxiv.org/html/2602.08643
February 10, 2026 at 6:53 AM
Max Rubinstein, Megan S. Schuler, Elizabeth A. Stuart, Bradley D. Stein, Max Griswold, Elizabeth M. Stone, Beth Ann Griffin: State policy heterogeneity analyses: considerations and proposals https://arxiv.org/abs/2602.08643 https://arxiv.org/pdf/2602.08643 https://arxiv.org/html/2602.08643
Luca Presicce, Sudipto Banerjee: Adaptive Markovian Spatiotemporal Transfer Learning in Multivariate Bayesian Modeling https://arxiv.org/abs/2602.08544 https://arxiv.org/pdf/2602.08544 https://arxiv.org/html/2602.08544
February 10, 2026 at 6:53 AM
Luca Presicce, Sudipto Banerjee: Adaptive Markovian Spatiotemporal Transfer Learning in Multivariate Bayesian Modeling https://arxiv.org/abs/2602.08544 https://arxiv.org/pdf/2602.08544 https://arxiv.org/html/2602.08544
Xiang Ye, Janet Van Niekerk, Haavard Rue: A Bayesian regression framework for circular models with INLA https://arxiv.org/abs/2602.08413 https://arxiv.org/pdf/2602.08413 https://arxiv.org/html/2602.08413
February 10, 2026 at 6:53 AM
Xiang Ye, Janet Van Niekerk, Haavard Rue: A Bayesian regression framework for circular models with INLA https://arxiv.org/abs/2602.08413 https://arxiv.org/pdf/2602.08413 https://arxiv.org/html/2602.08413
Takato Hashino, Koji Tsukuda: Estimating the Shannon Entropy Using the Pitman--Yor Process https://arxiv.org/abs/2602.08347 https://arxiv.org/pdf/2602.08347 https://arxiv.org/html/2602.08347
February 10, 2026 at 6:53 AM
Takato Hashino, Koji Tsukuda: Estimating the Shannon Entropy Using the Pitman--Yor Process https://arxiv.org/abs/2602.08347 https://arxiv.org/pdf/2602.08347 https://arxiv.org/html/2602.08347
Jacob Tennenbaum, Adam Kapelner: Improved Conditional Logistic Regression using Information in Concordant Pairs with Software https://arxiv.org/abs/2602.08212 https://arxiv.org/pdf/2602.08212 https://arxiv.org/html/2602.08212
February 10, 2026 at 6:53 AM
Jacob Tennenbaum, Adam Kapelner: Improved Conditional Logistic Regression using Information in Concordant Pairs with Software https://arxiv.org/abs/2602.08212 https://arxiv.org/pdf/2602.08212 https://arxiv.org/html/2602.08212
Juan Carlos Escanciano, Jacobo de U\~na-\'Alvarez: Goodness-of-Fit Tests for Censored and Truncated Data: Maximum Mean Discrepancy Over Regular Functionals https://arxiv.org/abs/2602.08108 https://arxiv.org/pdf/2602.08108 https://arxiv.org/html/2602.08108
February 10, 2026 at 6:53 AM
Juan Carlos Escanciano, Jacobo de U\~na-\'Alvarez: Goodness-of-Fit Tests for Censored and Truncated Data: Maximum Mean Discrepancy Over Regular Functionals https://arxiv.org/abs/2602.08108 https://arxiv.org/pdf/2602.08108 https://arxiv.org/html/2602.08108
Brian M Cho, Raaz Dwivedi, Nathan Kallus: GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function https://arxiv.org/abs/2602.08096 https://arxiv.org/pdf/2602.08096 https://arxiv.org/html/2602.08096
February 10, 2026 at 6:53 AM
Brian M Cho, Raaz Dwivedi, Nathan Kallus: GAAVI: Global Asymptotic Anytime Valid Inference for the Conditional Mean Function https://arxiv.org/abs/2602.08096 https://arxiv.org/pdf/2602.08096 https://arxiv.org/html/2602.08096
John W. Jackson, Ting-Hsuan Chang, Aster Meche, Trang Q. Nguyen: Estimation Strategies for Causal Decomposition Analysis with Allowability Specifications https://arxiv.org/abs/2602.07825 https://arxiv.org/pdf/2602.07825 https://arxiv.org/html/2602.07825
February 10, 2026 at 6:53 AM
John W. Jackson, Ting-Hsuan Chang, Aster Meche, Trang Q. Nguyen: Estimation Strategies for Causal Decomposition Analysis with Allowability Specifications https://arxiv.org/abs/2602.07825 https://arxiv.org/pdf/2602.07825 https://arxiv.org/html/2602.07825
Buddhananda Banerjee, Surojit Biswas, Daitari Prusty: Hyperbolic statistical inference for Treatment Effects with Circular biomarker of astigmatism https://arxiv.org/abs/2602.07740 https://arxiv.org/pdf/2602.07740 https://arxiv.org/html/2602.07740
February 10, 2026 at 6:53 AM
Buddhananda Banerjee, Surojit Biswas, Daitari Prusty: Hyperbolic statistical inference for Treatment Effects with Circular biomarker of astigmatism https://arxiv.org/abs/2602.07740 https://arxiv.org/pdf/2602.07740 https://arxiv.org/html/2602.07740
Chak Kwong (Tommy), Cheng, Hakan Demirtas: Generation of Multivariate Discrete Data with Generalized Poisson, Negative Binomial and Binomial Marginal Distributions https://arxiv.org/abs/2602.07707 https://arxiv.org/pdf/2602.07707 https://arxiv.org/html/2602.07707
February 10, 2026 at 6:53 AM
Chak Kwong (Tommy), Cheng, Hakan Demirtas: Generation of Multivariate Discrete Data with Generalized Poisson, Negative Binomial and Binomial Marginal Distributions https://arxiv.org/abs/2602.07707 https://arxiv.org/pdf/2602.07707 https://arxiv.org/html/2602.07707