Symbolic regression is emerging as a promising machine learning method for learning
succinct underlying interpretable mathematical expressions directly from data. Whereas it …

Understanding the predictions of a machine learning model can be as crucial as the model's
accuracy in many application domains. However, the black-box nature of most highly …

Starting from the first renormalized factorization theorem for a process described at
subleading power in soft-collinear effective theory, we discuss the resummation of Sudakov …

A bstract We investigate the swampland distance conjecture (SDC) in the complex moduli
space of type II compactifications on one-parameter Calabi-Yau threefolds. This class of …

The WIMPzilla hypothesis is that the dark matter is a super-weakly-interacting and
superheavy particle. Conventionally, the WIMPzilla abundance is set by gravitational particle …

Abstract Akemann, Ipsen and Kieburg recently showed that the squared singular values of
products of M rectangular random matrices with independent complex Gaussian entries are …

Recent works on Bayesian neural networks (BNNs) have highlighted the need to better
understand the implications of using Gaussian priors in combination with the compositional …

Nonlinear Systems and Their Remarkable Mathematical Structures, Volume 1 aims to
describe the recent progress in nonlinear differential equations and nonlinear dynamical …

A bstract Soft functions defined in terms of matrix elements of soft fields dressed by Wilson
lines are central components of factorization theorems for cross sections and decay rates in …

We develop a resummation approach based on Meijer-G functions and apply it to
approximate the Borel sum of divergent series and the Borel-Écalle sum of resurgent …