Results 21 to 30 of about 19,618 (150)
Entanglement renormalization and integral geometry
We revisit the applications of integral geometry in AdS$_3$ and argue that the metric of the kinematic space can be realized as the entanglement contour, which is defined as the additive entanglement density.
Huang, Xing, Lin, Feng-Li
core +1 more source
Variational Autoencoder+Deep Deterministic Policy Gradient addresses low‐light failures of infrared depth sensing for indoor robot navigation. Stage 1 pretrains an attention‐enhanced Variational Autoencoder (Convolutional Block Attention Module+Feature Pyramid Network) to map dark depth frames to a well‐lit reconstruction, yielding a 128‐D latent code ...
Uiseok Lee +7 more
wiley +1 more source
A computational framework for optimizing strain sensor placement in wearable motion tracking systems is presented. By combining dense strain mapping with a genetic algorithm, the method discovers counterintuitive yet highly effective configurations that reduce joint angle error by 32%.
Minu Kim +4 more
wiley +1 more source
On a Gromoll-Meyer type theorem in globally hyperbolic stationary spacetimes
Following the lines of the celebrated Riemannian result of Gromoll and Meyer, we use infinite dimensional equivariant Morse theory to establish the existence of infinitely many geometrically distinct closed geodesics in a class of globally hyperbolic ...
Biliotti, L., Mercuri, F., Piccione, P.
core +1 more source
Uncertainty Calibration in Molecular Machine Learning: Comparing Evidential and Ensemble Approaches
Raw uncertainty estimates from deep evidential regression and deep ensembles are systematically miscalibrated. Post hoc calibration aligns predicted uncertainty with true errors, improving reliability and enabling efficient active learning and reducing computational cost while preserving predictive accuracy.
Bidhan Chandra Garain +3 more
wiley +1 more source
ABSTRACT Nowadays, a substantial portion of investigations concerning the symmetry analysis of differential equations predominantly adhere to a framework comprising the following key procedures: (i) the derivation of symmetries, (ii) the determination of an optimal system, (iii) the utilization of these symmetries to construct invariants or ...
A. Paliathanasis +2 more
wiley +1 more source
The single‐scan approach to terrestrial laser scanning (TLS) and the self‐terrain‐normalized form of drone‐based digital aerial photogrammetry (DAP) offer practical options for rapid assessment of the vegetation structure in tropical landscapes.
Magnus Onyiriagwu +7 more
wiley +1 more source
Predation by pine martens Martes martes and red foxes Vulpes vulpes is an important factor influencing the population dynamics of capercaillie Tetrao urogallus. However, there is a knowledge gap regarding the relative effects of these mesopredators on the reproductive success of capercaillie. To better understand how various landscape factors influence
Siow Yan Jennifer Angoh +4 more
wiley +1 more source
SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier +5 more
wiley +1 more source
A Non‐Parametric Framework for Correlation Functions on Product Metric Spaces
Summary We propose a non‐parametric framework for analysing data defined over products of metric spaces, a versatile class encountered in various fields. This framework accommodates non‐stationarity and seasonality and is applicable to both local and global domains, such as the Earth's surface, as well as domains evolving over linear time or time ...
Pier Giovanni Bissiri +3 more
wiley +1 more source

