Qijun Chen, Shaofan Li eXact-Prior Variational Autoencoder (X-VAE): Learning Data-Adaptive Gaussian Mixture Priors for Latent Distributions https://arxiv.org/abs/2607.01275

Stefano Masini, Cecilia Viscardi, Michela Baccini Full Bayesian Reinforcement Learning via LF-IBIS https://arxiv.org/abs/2607.01741

Xin Guan Statistical Properties of $k$-means Clustering for Data Missing Completely at Random https://arxiv.org/abs/2607.01945

Julian Cardenas, Jamie Arjona, Pedro Delicado Autorelevance function and other feature relevance measures for univariate time series https://arxiv.org/abs/2607.01959

Matej Benko, Pierre Bousquet, Iwona Chlebicka, B{\l}a\.zej Miasojedow Born Discrete, Made Smooth: Variational Formulation of Shallow Neural Networks https://arxiv.org/abs/2607.02003

Yurui Zheng, Ying Jin Prediction Sets for Counterfactual Decisions: Coverage, Optimality, and Conformal Prediction https://arxiv.org/abs/2607.02206

Sampreeti Bhattacharya, Arkaprava Roy An Additive MLP-GNN Framework for Characterizing Chemical and Structural Contributions to Aqueous Solubility https://arxiv.org/abs/2607.02212

Yuan Yuan The Dual Nature of LLM Persona: Aggregated Tendencies and Frame-Dependent Geometry https://arxiv.org/abs/2607.02368

Konstantin H\"aberle, Helmut B\"olcskei Separation Capacity of Scattering Networks https://arxiv.org/abs/2606.30822

Abigail Loe, Susan Murry, Zhenke Wu Dynamic Prediction of Alternating Recurrent Events via Neural Network https://arxiv.org/abs/2606.30889

Konstantinos Emmanouilidis, Lachlan MacDonald, Salma Tarmoun, Rene Vidal SGD at the Edge of Stability: Stochastic Stabilization with Large Learning Rates https://arxiv.org/abs/2606.30930

Rui-Yang Zhang, Lachlan Astfalck, Edward Cripps, David Leslie, Henry Moss Dynamic Gaussian Processes and the Vanilla-SPDE Exchange https://arxiv.org/abs/2606.31063

Xin Guan MNAR-$k$-means: A $k$-means Clustering for Data Missing Not at Random with Magnitude-Decaying Probability https://arxiv.org/abs/2606.31253

Jiachen Cong, Jingbo Liu Accelerating Conformal Prediction via Approximate Leave-One-Out https://arxiv.org/abs/2606.31915

Rasoul Shafipour, Andrei Buciulea, Santiago Segarra, Antonio G. Marques, Gonzalo Mateos Directed Graph Topology Inference via Graph Filter Identification https://arxiv.org/abs/2606.27455

Xavier Fonseca The Decision Geometry of Covariance Estimation for the Global Minimum-Variance Portfolio under Heavy Tails https://arxiv.org/abs/2606.27462

Shixiang Liu, Hanming Yang Adversarial Contamination Meets Hard Thresholding: An Iterative Algorithm with Signal Adaptivity and Minimax Optimality https://arxiv.org/abs/2606.27685

Jiayao Bai, Lang Deng, Yi Du, Yifei Jia Local Fokker--Planck Geometry for Score Estimation: Heat-Ball Mean-Value Representations and Exact High-Dimensional Sampling https://arxiv.org/abs/2606.27954

Shai Ben-David, Farnam Mansouri, Anay Mehrotra, Manolis Zampetakis Surprises in Proper Positive-Only Learning https://arxiv.org/abs/2606.28309

Nasrin Malekzadeh Goradel, Niccolo Pancino, Yaser Gholizade Atani, Benedetta Tondi, Giovanni Bellettini, Mauro Barni The Role of Input Dimensionality in the Emergence and Targeted Control of Adversarial Examples https://arxiv.org/abs/2606.26207

Daniel Corrales, David R\'ios Insua A probabilistic framework for online test-time adaptation https://arxiv.org/abs/2606.26457

Minghao Chen, Jiale Zheng XMSE-Aware Adaptive Empirical Bayes Estimation https://arxiv.org/abs/2606.26975

Hanli Xu, Fengxiang He, Sarat Moka Beyond Global Divergences: A Local-Mass Perspective on Bayesian Inference https://arxiv.org/abs/2606.27090

Graham Gibson, John Tipton, Kellin Rumsey, Natalie Klein Ribbon: Scalable Approximation and Robust Uncertainty Quantification https://arxiv.org/abs/2606.27269

Johannes Zenn, Jonas Geiping When are likely answers right? On Sequence Probability and Correctness in LLMs https://arxiv.org/abs/2606.27359

Weihao Li, Dianne Cook, Emi Tanaka, Susan VanderPlas, Klaus Ackermann Automated Residual Plot Assessment With the R Package autovi and the Shiny Application autovi.web https://arxiv.org/abs/2606.24236

Giorgio Corani, Stefano Damato, Dario Azzimonti, Lorenzo Zambon Model selection with proper scoring rules on data sets of time series https://arxiv.org/abs/2606.24715

Ziheng Wei, Annie Qu, Rui Miao Off-Policy Evaluation for Missingness-Aware Policies in MDPs with Rewards Missing Not at Random https://arxiv.org/abs/2606.20206

Potito Aghilar, Sabino Roccotelli, Stanislao Fidanza, Vito Walter Anelli, Sebastiano Stramaglia, Tommaso Di Noia The Representational Limit of Scalar Interactions: An Interventional Decomposition https://arxiv.org/abs/2606.19410

Beichen Wan, Mo Liu A Solver-Free Training Method for Predict-then-Optimize https://arxiv.org/abs/2606.19587

Julie Fendler, Francesca L. Crowe, Tom Marshall, Sylvia Richardson, Paul D. W. Kirk Variational Consensus Monte Carlo for Bayesian Mixture https://arxiv.org/abs/2606.19643

Zilong Zhang, Yi-Ting Hung, Weiyi He, Junxi Zhang, Lei Ding, Chi-Kuang Yeh AURA: Adaptive Uncertainty-aware Refinement for LLM-as-a-Judge Auditing https://arxiv.org/abs/2606.19714

Haonan Xu, Yingying Li Stochastic Linear Contextual Bandits with Bounded Noise: A Set-Membership Approach https://arxiv.org/abs/2606.20022

Edgar Jaber (CB,ENS Paris Saclay), Vincent Chabridon (EDF R\&D PRISME), Mathilde Mougeot (CB,ENSIIE,ENS Paris Saclay) AK-MCS-C2 : Active Kriging Monte Carlo Simulation method with conformal certification for failure probability estimation https://arxiv.org/abs/2606.20191

Itay Lavie, Noam Levi, Yonatan Kahn Statistical Properties of Training & Generalization https://arxiv.org/abs/2606.20299

Jie Min, Yueyao Wang, Mengkun Chen SSH-Net: A Deep Neural Network for Predicting Failure Time Distribution Functions under Competing Risks with Application to GPU Data https://arxiv.org/abs/2606.20451

Peng Xu, Changbo Zhu, Young-Heon Kim, Xiaohui Chen Another Look at Log-PCA for Probability Measures: A Dynamical Formulation and Statistical Convergence https://arxiv.org/abs/2606.17196

Jasper van Doornmalen, Mathieu Molina, Victor Verdugo, Jos\'e Verschae Tight $L_\infty$ Sample Complexity for Low-Degree and Sparse Boolean Polynomials https://arxiv.org/abs/2606.17319

Fangyuan Lin, Spencer Frei, Victor H. de la Pena Bounded Difference Concentration for Infinitely Exchangeable Sequences with Applications to AI Benchmark Uncertainty https://arxiv.org/abs/2606.17426

Adolphus Wagala, Mehmet Samur, Giovanni Parmigiani A Bayesian Boolean Matrix Factorization with Application to Copy Number Analysis in Cancer https://arxiv.org/abs/2606.17491

Arturo P\'erez-Peralta, Sandra Ben\'itez-Pe\~na, Blas Kolic, Rosa E. Lillo Geometrical fairness in graph neural networks https://arxiv.org/abs/2606.17684

Tomasz Maciazek Differential Privacy of Gaussian Process Posterior Sampling https://arxiv.org/abs/2606.17995

Eric V. Strobl Fast Nonparametric Conditional Independence Testing via Two-Stage Regression https://arxiv.org/abs/2606.18011

Nathan Ouyang, Kexin Wan, Anna Seigal Tensor-based second-order causal discovery https://arxiv.org/abs/2606.18074

M. Forzo, E. Monzio Compagnoni, A. Russo, A. Pacchiano A Diffusion Approximation for Temporal-Difference Learning with Linear Features under Markovian Noise https://arxiv.org/abs/2606.18183

Yan Hong, Kedong Xiu, Wei Li, Jun Lan, Huijia Zhu, Shuheng Zhou, Zhongcai Lyu, Weiqiang Wang, Jianfu Zhang LoMC: Localized Multidirectional Correction for Refusal Suppression in Routed Foundation Models https://arxiv.org/abs/2606.13709

Na\"il B. Khelifa, Richard E. Turner, Ramji Venkataramanan Recursively Trained Diffusion Models: Limiting Collapse Distribution and Spectral Characterization https://arxiv.org/abs/2606.13796

Ousmane Amadou Dia Adaptive Nucleus Truncation for Long-Form Reasoning https://arxiv.org/abs/2606.13982

Mathias Bourel A General Framework for Decision Trees via Bregman Divergences https://arxiv.org/abs/2606.13984

Brian Britos, Mathias Bourel Geometric Domain Adaptation via Optimal Transport for Linear Regression in R^2 https://arxiv.org/abs/2606.14023