arXiv:2505.15808v2 Announce Type: replace-cross
Abstract: We present a neural framework for learning conditional optimal transport (OT) maps between probability distributions. Our approach introduces a conditioning mechanism capable of processing both…
arXiv:2505.21770v3 Announce Type: replace-cross
Abstract: Identifying the drift and diffusion of an SDE from its population dynamics is a notoriously challenging task. Researchers in machine learning and single-cell biology have only been able to prov…
arXiv:2604.00432v1 Announce Type: new
Abstract: We study the problem of reconstructing the latent geometry of a $d$-dimensional Riemannian manifold from a random geometric graph. While recent works have made significant progress in manifold recovery f…
arXiv:2604.00064v1 Announce Type: new
Abstract: We study trajectory forecasting under squared loss for time series with weak conditional structure, using highly expressive prediction models. Building on the classical characterization of squared-loss r…
arXiv:2604.00963v1 Announce Type: cross
Abstract: We show polylogarithmic mixing time bounds for the alternating-scan sampler for positively weighted restricted Boltzmann machines. This is done via analysing the same chain and the Glauber dynamics for…
arXiv:2501.09821v2 Announce Type: replace
Abstract: We introduce BN-Pool, the first clustering-based pooling method for Graph Neural Networks that adaptively determines the number of supernodes in a coarsened graph. BN-Pool leverages a generative mode…
arXiv:2603.29555v1 Announce Type: new
Abstract: Motivated by the success of score-based generative models, a number of diffusion-based algorithms have recently been proposed for the problem of sampling from a probability measure whose unnormalized den…
arXiv:2603.28956v1 Announce Type: cross
Abstract: The minimum-norm interpolator (MNI) framework has recently attracted considerable attention as a tool for understanding generalization in overparameterized models, such as neural networks. In this work…
arXiv:2603.26692v1 Announce Type: cross
Abstract: We introduce a new notion, that of a contextuality profile of a system. Rather than characterizing a system’s contextuality by a single number, its overall degree of contextuality, we show how it can b…
arXiv:2603.27370v1 Announce Type: cross
Abstract: This paper revisits and extends the 2013 development by Rockafellar and Uryasev of the Risk Quadrangle (RQ) as a unified scheme for integrating risk management, optimization, and statistical estimation…