Statistics Papers

ResNets of All Shapes and Sizes: Convergence of Training Dynamics in the Large-scale Limit Louis-Pierre Chaintron, Lénaïc Chizat, Javier Maas arxiv.org/abs/2603.18168 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

Starting Off on the Wrong Foot: Pitfalls in Data Preparation Jiayi Guo, Panyi Dong, Zhiyu Quan arxiv.org/abs/2603.18190 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚜𝚝𝚊𝚝.𝙰𝙿]

A Hybrid Conditional Diffusion-DeepONet Framework for High-Fidelity Stress Prediction in Hyperelastic Materials Purna Vindhya Kota, Meer Mehran Rashid, Somdatta Goswami, Lori Graham-Brady arxiv.org/abs/2603.18225 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

Multi-Domain Causal Empirical Bayes Under Linear Mixing Bohan Wu, Julius von Kügelgen, David M. Blei arxiv.org/abs/2603.18404 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚜𝚝𝚊𝚝.𝙼𝙴]

Statistical Testing Framework for Clustering Pipelines by Selective Inference Yugo Miyata, Tomohiro Shiraishi, Shunichi Nishino, Ichiro Takeuchi arxiv.org/abs/2603.18413 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

Precise Performance of Linear Denoisers in the Proportional Regime Reza Ghane, Danil Akhtiamov, Babak Hassibi arxiv.org/abs/2603.18483 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚖𝚊𝚝𝚑.𝙾𝙲]

On the Peril of (Even a Little) Nonstationarity in Satisficing Regret Minimization Yixuan Zhang, Ruihao Zhu, Qiaomin Xie arxiv.org/abs/2603.18514 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

A Theoretical Comparison of No-U-Turn Sampler Variants: Necessary and Su?cient Convergence Conditions and Mixing Time Analysis under Gaussian Targets Samuel Gruffaz, Kyurae Kim, Fares Guehtar, … arxiv.org/abs/2603.18640 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚖𝚊𝚝𝚑.𝙿𝚁]

SRRM: Improving Recursive Transport Surrogates in the Small-Discrepancy Regime Yufei Zhang, Tao Wang, Jingyi Zhang arxiv.org/abs/2603.18781 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚜𝚝𝚊𝚝.𝙰𝙿]

Kernel Single-Index Bandits: Estimation, Inference, and Learning Sakshi Arya, Satarupa Bhattacharjee, Bharath K. Sriperumbudur arxiv.org/abs/2603.18938 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚖𝚊𝚝𝚑.𝚂𝚃 𝚜𝚝𝚊𝚝.𝚃𝙷]

Unified Taxonomy for Multivariate Time Series Anomaly Detection using Deep Learning Bruna Alves, Armando J. Pinho, Sónia Gouveia arxiv.org/abs/2603.18941 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

Revisiting OmniAnomaly for Anomaly Detection: performance metrics and comparison with PCA-based models Bruna Alves, Ana Martins, Armando J. Pinho, Sónia Gouveia arxiv.org/abs/2603.18985 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

Fast and Interpretable Autoregressive Estimation with Neural Network Backpropagation Anaísa Lucena, Ana Martins, Armando J. Pinho, Sónia Gouveia arxiv.org/abs/2603.19041 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

The Exponentially Weighted Signature Alexandre Bloch, Samuel N. Cohen, Terry Lyons, Joël Mouterde, Benjamin Walker arxiv.org/abs/2603.19198 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

Kriging via variably scaled kernels Gianluca Audone, Francesco Marchetti, Emma Perracchione, Milvia Rossini arxiv.org/abs/2603.16950 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚜𝚝𝚊𝚝.𝙼𝙴]

Dependence Fidelity and Downstream Inference Stability in Generative Models Nazia Riasat arxiv.org/abs/2603.17041 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙰𝙸 𝚌𝚜.𝙻𝙶 𝚜𝚝𝚊𝚝.𝙼𝙴]

Self-Regularized Learning Methods Max Schölpple, Liu Fanghui, Ingo Steinwart arxiv.org/abs/2603.17160 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚖𝚊𝚝𝚑.𝚂𝚃 𝚜𝚝𝚊𝚝.𝚃𝙷]

Mirror Descent on Riemannian Manifolds Jiaxin Jiang, Lei Shi, Jiyuan Tan arxiv.org/abs/2603.17527 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶 𝚖𝚊𝚝𝚑.𝙾𝙲]

Consistency of the k-Nearest Neighbor Regressor under Complex Survey Designs Caren Hasler arxiv.org/abs/2603.17551 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]

Gaussian Process Limit Reveals Structural Benefits of Graph Transformers Nil Ayday, Lingchu Yang, Debarghya Ghoshdastidar arxiv.org/abs/2603.17569 [𝚜𝚝𝚊𝚝.𝙼𝙻 𝚌𝚜.𝙻𝙶]