Aaron Pim, Tristan Pryer Surrogate Modelling of Proton Dose with Monte Carlo Dropout Uncertainty Quantification https://arxiv.org/abs/2509.18155

Saptati Datta, Nicolas W. Hengartner, Yulia Pimonova, Natalie E. Klein, Nicholas Lubbers Statistical Insight into Meta-Learning via Predictor Subspace Characterization and Quantification of Task Diversity https://arxiv.org/abs/2509.18349

Xiaogang Su End-Cut Preference in Survival Trees https://arxiv.org/abs/2509.18477

Yuanchen Wu, Yubai Yuan Estimating Heterogeneous Causal Effect on Networks via Orthogonal Learning https://arxiv.org/abs/2509.18484

Christos Revelas, Otilia Boldea, Bas J. M. Werker Consistency of Selection Strategies for Fraud Detection https://arxiv.org/abs/2509.18739

Muhammad Rana, Keaton Hamm Neighbor Embeddings Using Unbalanced Optimal Transport Metrics https://arxiv.org/abs/2509.19226

Muhammad Rana, Abiy Tasissa, HanQin Cai, Yakov Gavriyelov, Keaton Hamm Recovering Wasserstein Distance Matrices from Few Measurements https://arxiv.org/abs/2509.19250

Tim Y. J. Wang, O. Deniz Akyildiz A Gradient Flow Approach to Solving Inverse Problems with Latent Diffusion Models https://arxiv.org/abs/2509.19276

Jiahao Zhang, Shiheng Zhang, Guang Lin Low-Rank Adaptation of Evolutionary Deep Neural Networks for Efficient Learning of Time-Dependent PDEs https://arxiv.org/abs/2509.16395

Anh Tuan Bui Conditional Multidimensional Scaling with Incomplete Conditioning Data https://arxiv.org/abs/2509.16627

Xiaoping Du System-Level Uncertainty Quantification with Multiple Machine Learning Models: A Theoretical Framework https://arxiv.org/abs/2509.16663

Alex Luedtke, Kenji Fukumizu DoubleGen: Debiased Generative Modeling of Counterfactuals https://arxiv.org/abs/2509.16842

Jingfeng Wu, Peter L. Bartlett, Jason D. Lee, Sham M. Kakade, Bin Yu Risk Comparisons in Linear Regression: Implicit Regularization Dominates Explicit Regularization https://arxiv.org/abs/2509.17251

Shivam Kumar, Haotian Xu, Carlos Misael Madrid Padilla, Yuehaw Khoo, Oscar Hernan Madrid Padilla, Daren Wang Bias-variance Tradeoff in Tensor Estimation https://arxiv.org/abs/2509.17382

Siqi Li, Molei Liu, Ziye Tian, Chuan Hong, Nan Liu Robust Mixture Models for Algorithmic Fairness Under Latent Heterogeneity https://arxiv.org/abs/2509.17411

Dominic Broadbent, Nick Whiteley, Robert Allison, Tom Lovett Bilateral Distribution Compression: Reducing Both Data Size and Dimensionality https://arxiv.org/abs/2509.17543

Mohammed Racim Moussa Boudjemaa, Alper Kalle, Xiaoyi Mai, Jos\'e Henrique de Morais Goulart, C\'edric F\'evotte Whitening Spherical Gaussian Mixtures in the Large-Dimensional Regime https://arxiv.org/abs/2509.17636

Fernando Llorente, Daniel Waxman, Sanket Jantre, Nathan M. Urban, Susan E. Minkoff Robust, Online, and Adaptive Decentralized Gaussian Processes https://arxiv.org/abs/2509.18011

Yidong Zhou, Su I Iao, Hans-Georg M\"uller Fr\'echet Geodesic Boosting https://arxiv.org/abs/2509.18013

Amparo Ba\'illo, Jose R. Berrendero, Mart\'in S\'anchez-Signorini Kernel K-means clustering of distributional data https://arxiv.org/abs/2509.18037

Nicolas Salvad\'e, Tim Hillel Functional effects models: Accounting for preference heterogeneity in panel data with machine learning https://arxiv.org/abs/2509.18047

Chunna Li, Yiwei Song, Yuanhai Shao SETrLUSI: Stochastic Ensemble Multi-Source Transfer Learning Using Statistical Invariant https://arxiv.org/abs/2509.15593

Tiffany M. Tang, Elizaveta Levina, Ji Zhu Interpretable Network-assisted Random Forest+ https://arxiv.org/abs/2509.15611

Alexandra Carpentier, Christophe Giraud, Nicolas Verzelen Phase Transition for Stochastic Block Model with more than $\sqrt{n}$ Communities https://arxiv.org/abs/2509.15822

Bertrand Cloez, Adrien Cotil, Jean-Baptiste Menassol, Nicolas Verzelen Model-free algorithms for fast node clustering in SBM type graphs and application to social role inference in animals https://arxiv.org/abs/2509.15989

Lucas De Lara, Luca Ganassali What is a good matching of probability measures? A counterfactual lens on transport maps https://arxiv.org/abs/2509.16027

Xiaxue Ouyang, Xinlai Kang, Mengyu Li, Zhenxing Dou, Jun Yu, Cheng Meng A more efficient method for large-sample model-free feature screening via multi-armed bandits https://arxiv.org/abs/2509.16085

Zemin Xu, Wenbo Xie, Daiqian Xie, P. Hu Towards universal property prediction in Cartesian space: TACE is all you need https://arxiv.org/abs/2509.14961

M. Oguzhan Gultekin, Samet Demir, Zafer Dogan Learning Rate Should Scale Inversely with High-Order Data Moments in High-Dimensional Online Independent Component Analysis https://arxiv.org/abs/2509.15127

Yigit E. Yildirim, Samet Demir, Zafer Dogan Benefits of Online Tilted Empirical Risk Minimization: A Case Study of Outlier Detection and Robust Regression https://arxiv.org/abs/2509.15141

Jaeho Lee, Kangjin Kim, Gyeong Taek Lee Next-Depth Lookahead Tree https://arxiv.org/abs/2509.15143

Samet Demir, Zafer Dogan Asymptotic Study of In-context Learning with Random Transformers through Equivalent Models https://arxiv.org/abs/2509.15152

Marat Khusainov, Marina Sheshukova, Alain Durmus, Sergey Samsonov On the Rate of Gaussian Approximation for Linear Regression Problems https://arxiv.org/abs/2509.14039

Charuka D. Wickramasinghe, Krishanthi C. Weerasinghe, Pradeep K. Ranaweera PBPK-iPINNs : Inverse Physics-Informed Neural Networks for Physiologically Based Pharmacokinetic Brain Models https://arxiv.org/abs/2509.12666

Zhao Feng, Bicheng Yan, Luanxiao Zhao, Xianda Shen, Renyu Zhao, Wenhao Wang, Fengshou Zhang SURGIN: SURrogate-guided Generative INversion for subsurface multiphase flow with quantified uncertainty https://arxiv.org/abs/2509.13189

Tien-En Chang, Argon Chen Variable Selection Using Relative Importance Rankings https://arxiv.org/abs/2509.10853

Jia-Qi Yang, Lei Shi Kernel-based Stochastic Approximation Framework for Nonlinear Operator Learning https://arxiv.org/abs/2509.11070

Byungchang So Maximum diversity, weighting and invariants of time series https://arxiv.org/abs/2509.11146

Leon Chlon, Ahmed Karim, Maggie Chlon Predictable Compression Failures: Why Language Models Actually Hallucinate https://arxiv.org/abs/2509.11208

Zihan Dong, Xin Zhou, Ryumei Nakada, Lexin Li, Linjun Zhang Contrastive Network Representation Learning https://arxiv.org/abs/2509.11316

Rok Cestnik, Erik A. Martens Next-Generation Reservoir Computing for Dynamical Inference https://arxiv.org/abs/2509.11338

Chen Cheng, John Duchi Some Robustness Properties of Label Cleaning https://arxiv.org/abs/2509.11379

Kisung You A Particle-Flow Algorithm for Free-Support Wasserstein Barycenters https://arxiv.org/abs/2509.11435

Suman Cha, Hyunjoong Kim Learning Majority-to-Minority Transformations with MMD and Triplet Loss for Imbalanced Classification https://arxiv.org/abs/2509.11511

Davide La Vecchia, Hang Liu E-ROBOT: a dimension-free method for robust statistics and machine learning via Schr\"odinger bridge https://arxiv.org/abs/2509.11532

Rodrigue Govan (ISEA), Romane Scherrer (ISEA), Philippe Fournier-Viger (ISEA), Nazha Selmaoui-Folcher (ISEA) SpaPool: Soft Partition Assignment Pooling for__Graph Neural Networks https://arxiv.org/abs/2509.11675

Mika Sipil\"a, Klaus Nordhausen, Sara Taskinen Identifiable Autoregressive Variational Autoencoders for Nonlinear and Nonstationary Spatio-Temporal Blind Source Separation https://arxiv.org/abs/2509.11962

Francesco Amato, Julien Jacques MMM: Clustering Multivariate Longitudinal Mixed-type Data https://arxiv.org/abs/2509.12166

Argimiro Arratia, Alejandra Caba\~na, Ernesto Mordecki, Gerard Rovira-Parra The Morgan-Pitman Test of Equality of Variances and its Application to Machine Learning Model Evaluation and Selection https://arxiv.org/abs/2509.12185

Agus Sudjianto, Denis Burakov An Information-Theoretic Framework for Credit Risk Modeling: Unifying Industry Practice with Statistical Theory for Fair and Interpretable Scorecards https://arxiv.org/abs/2509.09855