Data Analysis, Statistics and Probability Papers of the Week

Existing hyperbolic embeddings represent network hierarchy and similarity through a few interpretable coordinates, but rely only on pairwise links: they cannot distinguish three units engaged in a common interaction from three units connected only in pairs. We introduce here the hyperbolic higher-order (HHO) embedding, which embeds a simplicial complex into the Poincaré disk, while incorporating its group interactions.

We develop a hierarchical Bayesian framework to infer the population properties of microlenses from an ensemble of microlensed GW events, constraining the slope of the power-law lens mass function ($\alpha_{\rm ML}$), the lens number density ($n_0$), and the fraction of dark matter in compact lenses ($f_{\rm DM}$).

In this work, we define a regional anomaly score by summing the squared latent coordinates of the same flow within small detector regions around the point where the particle enters the calorimeter, with the threshold set using background showers alone.

We construct a generative network for Monte-Carlo sampling in lattice field theories and beyond, for which the layerwise propagation is computed and optimised independently on each layer.

Using high-frequency sonic anemometer data from site-testing campaigns at the Giant Magellan Telescope (GMT) and Thirty Meter Telescope (TMT) sites in Chile, we apply detrended fluctuation analysis (DFA)---a technique from fractal time-series analysis---to identify the inertial sub-range and evaluate statistical isotropy in the ABL, comparing our approach with the Fourier-based algorithm for robust identification of the inertial subrange (ARIIS).

We introduce an observation-window analysis, in which prediction is evaluated as a function of observation time by providing models with the growth curve only up to progressively later times, to determine not only whether a property can be predicted, but when the necessary information becomes available during synthesis.

We present an automated photometric pipeline that identifies corotation radii by tracking the azimuthal phase offset between young and old stellar populations.

Battery capacity fade and corrosion-film growth depend on their history, so they are often modelled using general fractional calculus (GFC), where memory is described by an arbitrary Sonine kernel rather than a single power law. We tested this using two mechanistic models without fractional operators and de Levie's porous-electrode model, whose high-frequency order is exactly 0.5; our estimator recovered 0.500.

The candidates are the crossfade of independently drawn windows that the standard gravitational-wave libraries implement, overlap-save finite-impulse-response filtering, autoregressive and autoregressive moving-average (ARMA) models, and the reproducible filter of PyCBC.

We apply an integrated energy-balance workflow to five configurations tested by one rider on a road section.

As a remedy, we propose a machine-learning based retrieval concept and a preliminary architecture, framed as heterogeneous, multi-rate sensor fusion.

We introduce, by splitting the co-information into a pairwise maximum- entropy part and the third-order connected information, a PID that sits at zero overlap except when pairwise redundancy and triadic synergy coexist.

We present the Neural Density Model (NDM), a 3D density reanalysis for October 2003--October 2026 at 250--800~km.