arXiv:2603.25370v1 Announce Type: new
Abstract: Probabilistic forecasting provides a principled framework for uncertainty quantification in dynamical systems by representing predictions as probability distributions rather than deterministic trajectori…
arXiv:2603.25466v1 Announce Type: new
Abstract: We study statistical estimation in a student–teacher setting, where predictions from a pre-trained teacher are used to guide a student model. A standard approach is to train the student to directly matc…
arXiv:2603.25579v1 Announce Type: new
Abstract: A key capability of modern neural networks is their capacity to simultaneously learn underlying rules and memorize specific facts or exceptions. Yet, theoretical understanding of this dual capability rem…
arXiv:2603.25530v1 Announce Type: new
Abstract: Tensors provide a structured representation for multidimensional data, yet discretization can obscure important information when such data originates from continuous processes. We address this limitation…
arXiv:2603.24626v1 Announce Type: cross
Abstract: Single-cell RNA sequencing (scRNA-seq) is inherently affected by sparsity caused by dropout events, in which expressed genes are recorded as zeros due to technical limitations. These artifacts distort …
arXiv:2603.24613v1 Announce Type: cross
Abstract: Computational topology provides a tool, persistent homology, to extract quantitative descriptors from structured objects (images, graphs, point clouds, etc). These descriptors can then be involved in o…
arXiv:2603.25224v1 Announce Type: new
Abstract: Demographic parity (DP) is a widely used group fairness criterion requiring predictive distributions to be invariant across sensitive groups. While natural in classification, full distributional DP is of…
arXiv:2602.20844v2 Announce Type: replace-cross
Abstract: Stochastic network models play a central role across a wide range of scientific disciplines, and questions of statistical inference arise naturally in this context. In this paper we investigate…
arXiv:2603.25622v1 Announce Type: cross
Abstract: We present an efficient algorithm for uniformly sampling from an arbitrary compact body $\mathcal{X} \subset \mathbb{R}^n$ from a warm start under isoperimetry and a natural volume growth condition. Ou…
arXiv:2603.25397v1 Announce Type: cross
Abstract: In this applied paper, we address the difficult open problem of when to discharge patients from the Intensive Care Unit. This can be conceived as an optimal stopping scenario with three added challenge…