What fraction of the plane can be colored so that two colored points cannot be exactly a unit distance away from each other? This geometric question was formulated by Leo Moser in the early 1960s. According to a conjecture of Paul Erdős, this fraction must be less than ¼. The currently best lower bound of 0.2293 is given by a construction by Hallard Croft dating back to 1967. Several research groups have published partial results on the problem, gradually strengthening the initial upper density estimate of 0.

In this work, we present our reproducibility study of Label-Free Explainability for Unsupervised Models, a paper that introduces two post‐hoc explanation techniques for neural networks: (1) label‐free feature importance and (2) label‐free example importance. Our study focuses on the reproducibility of the authors’ most important claims: (i) perturbing features with the highest importance scores causes higher latent shift than perturbing random pixels, (ii) label‐free example importance scores help to identify training examples that are highly related to a given test example, (iii) unsupervised models trained on different tasks show moderate correlation among the highest scored features and (iv) low correlation in example scores measured on a fixed set of data points, and (v) increasing the disentanglement with β in a β‐VAE does not imply that latent units will focus on more different features.

We consider the minimum number of lines $h_n$ and $p_n$ needed to intersect or pierce, respectively, all the cells of the $n \times n$ chessboard. Determining these values can also be interpreted as a strengthening of the classical plank problem for integer points. Using the symmetric plank theorem of K. Ball, we prove that $h = \lceil \frac{n}{2} \rceil$ for each $n \leq 1$. Studying the piercing problem, we show that $0.

In this paper, the nilspace approach to higher-order Fourier analysis is developed in the setting of vector spaces over a prime field $\mathbb{F}_p$, with applications mainly in ergodic theory. A key requisite for this development is to identify a class of nilspaces adequate for this setting. We introduce such a class, whose members we call $p$-homogeneous nilspaces. One of our main results characterizes these objects in terms of a simple algebraic property.