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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Daniel McBride, Pratik Khandagale, Cristina Garcia-Cardona, Yen Ting Lin: Wasserstein Gradient Flows and Forward-Only Diffusion Are Not Enough for Multimodal Sampling arxiv.org/abs/2610.02081 arxiv.org/pdf/2610.02081 arxiv.org/html/2610.02081

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Zuokai Wen, Louis Grenioux, Weinan E, Jiequn Han: Error-Corrected Inference-Time Scaling for Imperfect Diffusion Models arxiv.org/abs/2610.01933 arxiv.org/pdf/2610.01933 arxiv.org/html/2610.01933

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Jorge Medina Moreira, Lorenzo Bardone, Lenka Zdeborov\'a: The hidden advantage of mask resampling: a theory of masked autoencoders arxiv.org/abs/2610.01578 arxiv.org/pdf/2610.01578 arxiv.org/html/2610.01578

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Leyang Wang, Yakun Wang, Song Liu, Taiji Suzuki: Zero Flux: Flow-Based Comparison of High-Dimensional Discrete Distributions arxiv.org/abs/2610.01472 arxiv.org/pdf/2610.01472 arxiv.org/html/2610.01472

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Yujie Zhu, Charles A. Hepburn, Matthew Thorpe, Giovanni Montana: Optimal Transport Meets Reinforcement Learning: A Survey arxiv.org/abs/2610.01413 arxiv.org/pdf/2610.01413 arxiv.org/html/2610.01413

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Hoang Phuc Hau Luu, Marcelo Hartmann, Zhongjian Wang: Posterior sampling by source-space MCMC via prior-based few-step transport maps arxiv.org/abs/2610.01034 arxiv.org/pdf/2610.01034 arxiv.org/html/2610.01034

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Jie Tang, Chuanlong Xie, Lixing Zhu: Tolerance-Based Fairness Auditing: Violation Certification and Sensitivity Screening arxiv.org/abs/2610.01005 arxiv.org/pdf/2610.01005 arxiv.org/html/2610.01005

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Marco Pollanen: The Price of Correlated Tests: How Strict Should a Model Release Gate Be? arxiv.org/abs/2610.00993 arxiv.org/pdf/2610.00993 arxiv.org/html/2610.00993

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Taehyun Hwang, Hyunjun Choi, Heesang Ann, Min-hwan Oh: Block Optimism for Nonstationary Bandits with Latent Linear Dynamics arxiv.org/abs/2610.00911 arxiv.org/pdf/2610.00911 arxiv.org/html/2610.00911

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

J. H. Ramirez-Gonzalez: Inference for stochastic differential equations driven by weighted sub-fractional Brownian motion using neural networks and the Euler approximation arxiv.org/abs/2610.00793 arxiv.org/pdf/2610.00793 arxiv.org/html/2610.00793

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Jing Shang, Mohammad Mehrabi, Xinyang Zhou, Mahmoud Saleh, Andrey Bernstein, Stefan Wager: Learning to Price Electricity for Optimal Demand Response arxiv.org/abs/2610.00755 arxiv.org/pdf/2610.00755 arxiv.org/html/2610.00755

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Carrie J. Lei-Cramer, Michael S. Jones, Laura J. Wendelberger: Adaptive Conformal Prediction for Image Regression Models with Application to an Inertial Confinement Fusion Emulator arxiv.org/abs/2610.00535 arxiv.org/pdf/2610.00535 arxiv.org/html/2610.00535

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Mauricio Herrera-Mar\'in: Fractional Laplace Neural Operators: Exact Architectures, an Expressivity Frontier at Criticality, and Certified Stability for Memory-Driven Network Dynamics arxiv.org/abs/2610.00515 arxiv.org/pdf/2610.00515 arxiv.org/html/2610.00515

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Hang Yin, Haozhe Wang, Yuhua Luo, Zhangqi Pan, Xiaoxing Wang, Junchi Yan: ChainLoRA: Geometry-Preserving Task Vector Merging for Continual Learning in LLMs arxiv.org/abs/2610.00431 arxiv.org/pdf/2610.00431 arxiv.org/html/2610.00431

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Qinchuan Cheng, Jiaqi Liu, Ruixuan Xie: Target-Dependent Limits of Causal Repair: A Leading-Log Frontier in a Gaussian Model arxiv.org/abs/2610.00424 arxiv.org/pdf/2610.00424 arxiv.org/html/2610.00424

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Loevenich, Moehlenhof, Holz, Schwarzer, Huerten, Lopes: Learning to Cover Locally: Graph Neural Combinatorial Optimization under a Hard Information Horizon arxiv.org/abs/2610.00422 arxiv.org/pdf/2610.00422 arxiv.org/html/2610.00422

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Yuxin Ma, Adir Dayan, Yam Eitan, Haggai Maron, Soledad Villar: Transferable Graph Metanetworks arxiv.org/abs/2610.00420 arxiv.org/pdf/2610.00420 arxiv.org/html/2610.00420

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

Zhongxuan Liu, Hongzhi Wang: Weighted Data Selection: Sharp Upper-Half and Five-Dimensional Laws arxiv.org/abs/2610.00101 arxiv.org/pdf/2610.00101 arxiv.org/html/2610.00101

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 02/10/2026

[2026-10-02 Fri (UTC), 18 new articles found for statML Machine Learning]

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Sundeep Prabhakar Chepuri, Antonio G. Marques, Maulik Devmurari, Gonzalo Mateos: Signal Processing over Product DAGs: Causal Shifts and Filters arxiv.org/abs/2609.40275 arxiv.org/pdf/2609.40275 arxiv.org/html/2609.40275

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Yonghan Jung: Proximal Balancing for Causal Effect Estimation under Unmeasured Confounding arxiv.org/abs/2609.40051 arxiv.org/pdf/2609.40051 arxiv.org/html/2609.40051

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Daniel Habermann, Andreas Bulling, Stefan T. Radev, Paul-Christian B\"urkner: Amortized Bayesian Inference on Multilevel Models of Arbitrary Structure arxiv.org/abs/2609.40024 arxiv.org/pdf/2609.40024 arxiv.org/html/2609.40024

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Chenglin Li, Qiao Liu: BayesNDE: Bayesian Generative Modeling for Neural Density Estimation arxiv.org/abs/2609.39843 arxiv.org/pdf/2609.39843 arxiv.org/html/2609.39843

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Xabier de Juan, Santiago Mazuelas, Yilun Zhu, Clayton Scott: Estimation of the Label-Noise Transition Matrix with Performance Guarantees via Selective Classification arxiv.org/abs/2609.39829 arxiv.org/pdf/2609.39829 arxiv.org/html/2609.39829

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Olischl\"ager, Jedhoff, Kucharsk\'y, Mishra, Radev, B\"urkner: Mitigating Representation Gaps in Amortized Bayesian Inference with Auxiliary Supervision arxiv.org/abs/2609.39525 arxiv.org/pdf/2609.39525 arxiv.org/html/2609.39525

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Maxx Richard Rahman, Mostafa Hammouda, Wolfgang Maass: CAMOS: Coupled Oscillatory State-Space Model for Multimodal Clinical Time-Series arxiv.org/abs/2609.39484 arxiv.org/pdf/2609.39484 arxiv.org/html/2609.39484

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Elis Stefansson, David V\"avinggren, Ant\^onio H. Ribeiro: Distributionally robust linear regression through the lens of adversarial training arxiv.org/abs/2609.39449 arxiv.org/pdf/2609.39449 arxiv.org/html/2609.39449

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Juno Kim, Hengyu Fu, Peter Bartlett, Jason D. Lee, Jingfeng Wu: Principal Component Regression Dominates all Monotone Spectral Filters for Linear Regression arxiv.org/abs/2609.39440 arxiv.org/pdf/2609.39440 arxiv.org/html/2609.39440

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Yuxuan Han, Xiaoyu Fan, Jiawei Zhang, Zhengyuan Zhou: Towards Optimal Inventory Control under Censored Demand: A Biased Sample-Average Approximation Approach arxiv.org/abs/2609.39397 arxiv.org/pdf/2609.39397 arxiv.org/html/2609.39397

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Th\'eo Marchetta, Filippo Alessandroni, Alessandro Breccia, Alessandro Ingrosso, Federica Gerace: A Dynamical Theory of LoRA in Continual Learning arxiv.org/abs/2609.39367 arxiv.org/pdf/2609.39367 arxiv.org/html/2609.39367

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Euijong Song, Hyewon Park, Gunwoong Park: Discrete Score Matching Enables Causal Discovery from Count Data arxiv.org/abs/2609.39326 arxiv.org/pdf/2609.39326 arxiv.org/html/2609.39326

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Baptiste Ferrere, Fabrice Gamboa, Jean-Michel Loubes: Minimax Additive Regression under Unknown Dependent Designs arxiv.org/abs/2609.39212 arxiv.org/pdf/2609.39212 arxiv.org/html/2609.39212

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Yugo Nakayama: Asymptotic Properties of Support Vector Machines in High-Dimension, Low-Sample-Size Settings under a Spiked Model arxiv.org/abs/2609.39173 arxiv.org/pdf/2609.39173 arxiv.org/html/2609.39173

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Takakura, Wachi, Higuchi, Miyaguchi, Suzuki: Steepest Guidance: A Practical and Principled Approach to Inference-Time Alignment of Flow and Diffusion-based Models arxiv.org/abs/2609.39091 arxiv.org/pdf/2609.39091 arxiv.org/html/2609.39091

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Songqiu Ma, Yunfei Yang: Minimax rates for learning spectral Barron functions by deep ReLU neural networks arxiv.org/abs/2609.39020 arxiv.org/pdf/2609.39020 arxiv.org/html/2609.39020

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Wilson G. Gregory, George A. Kevrekidis, Ben Blum-Smith, Soledad Villar: Warm-starting PDE solvers with any-dimensional machine learning arxiv.org/abs/2609.38916 arxiv.org/pdf/2609.38916 arxiv.org/html/2609.38916

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Kaixuan Ji, Qiwei Di, Qingyue Zhao, Heyang Zhao, Quanquan Gu: Bandits with Multiple Optimal Arms: Minimax Regret and Non-Adaptivit arxiv.org/abs/2609.38659 arxiv.org/pdf/2609.38659 arxiv.org/html/2609.38659

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Michael Wieck-Sosa, Cosma Rohilla Shalizi: Generative sequence modeling for infinite memory processes via predictive states arxiv.org/abs/2609.38524 arxiv.org/pdf/2609.38524 arxiv.org/html/2609.38524

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Ouyang, Wan, Haris, Tan, Peng, Li, Lin, Chen, Karimzadehgan, Go, Michailidis: Acceleration of Diffusion Language Model through Discrete Average Generator arxiv.org/abs/2609.38364 arxiv.org/pdf/2609.38364 arxiv.org/html/2609.38364

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

Daniela De Canditiis, Italia De Feis, Paola Stolfi: Robust LassoNet: Enhancing Feature Selection in Neural Networks via Robust Loss Functions arxiv.org/abs/2609.38263 arxiv.org/pdf/2609.38263 arxiv.org/html/2609.38263

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 01/10/2026

[2026-10-01 Thu (UTC), 23 new articles found for statML Machine Learning]

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Bruno Marcondes e Resende, Helton Graziadei, Thiago Rodrigo Ramos, Rafael Izbicki: ReCIRC: Rectified Conformal Risk Control arxiv.org/abs/2609.38112 arxiv.org/pdf/2609.38112 arxiv.org/html/2609.38112

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Chlo\'e Hashimoto-Cullen, Amaury Durand, Laurent Bozzi, Benjamin Guedj, Yannig Goude, Sylvain Le Corff: Latent Inference-Time Guidance of Time Series Foundation Models arxiv.org/abs/2609.38058 arxiv.org/pdf/2609.38058 arxiv.org/html/2609.38058

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Julien Boussard, Antoine D\'{e}bouchage, Th\'{e}o Saulus: Identifiability Guarantees for Drivers and Dynamics of Delayed Physical Systems arxiv.org/abs/2609.37944 arxiv.org/pdf/2609.37944 arxiv.org/html/2609.37944

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Cao Le Cong Thanh, Dang Quang Vinh, Vo Nguyen Le Duy: Post-Anomaly Detection Inference for Deep SVDD arxiv.org/abs/2609.37935 arxiv.org/pdf/2609.37935 arxiv.org/html/2609.37935

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Gwendal Debaussart-Joniec (CB, ENS Paris Saclay), Th\'eau Blanchard (HeKA | U1346, GE Healthcare), Argyris Kalogeratos (CB, ENS Paris Saclay): A Finslerian Approach for Embedding Directed Data arxiv.org/abs/2609.37649 arxiv.org/pdf/2609.37649 arxiv.org/html/2609.37649

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Attila Lovas, L\'or\'ant Nagy: Ornstein-Uhlenbeck Is Hard to Beat, Yet Superlinear Drift Ships Lower Transport Costs arxiv.org/abs/2609.37579 arxiv.org/pdf/2609.37579 arxiv.org/html/2609.37579

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arXiv stat.ML Machine Learning @statml-bot.bsky.social · 30/09/2026

Futoshi Futami, Jerry Huang, Ichiro Takeuchi: Hierarchical Utility Calibration for Structured Multiclass Decisions arxiv.org/abs/2609.36532 arxiv.org/pdf/2609.36532 arxiv.org/html/2609.36532

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