Results 61 to 70 of about 9,754 (219)
The Information Geometry of Sensor Configuration
In problems of parameter estimation from sensor data, the Fisher information provides a measure of the performance of the sensor; effectively, in an infinitesimal sense, how much information about the parameters can be obtained from the measurements ...
Simon Williams +3 more
doaj +1 more source
A 4D geometric morphometrics workflow to quantify complex biological motion
Abstract Quantifying biological motion is fundamentally tied to quantifying the biological structures that produce that motion. Yet, this dependence makes it essential to decouple motion from static morphology to enable general, comparable analyses across individuals and conditions. In this work, we present a methodological pipeline to study biological
Marta Gómez‐Recio +8 more
wiley +1 more source
Fractons, non-Riemannian geometry, and double field theory
We initiate a systematic study of fracton physics within the geometric framework of double field theory. We ascribe the immobility and large degeneracy of the former to the non-Riemannian backgrounds of the latter, in terms of generalized geodesics and ...
Stephen Angus +2 more
doaj +1 more source
Calibrating Bayesian inference
Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu +2 more
wiley +1 more source
Properties of infinite harmonic functions relative to Riemannian vector fields
We employ Riemannian jets which are adapted to the Riemannian geometry to obtain the existence-uniqueness of infinite harmonic functions in Riemannian spaces. We then show such functions are equivalent to those that enjoy comparison with Riemannian cones.
Thomas Bieske
doaj
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
An introduction to Smarandache multi-spaces and mathematical combinatorics [PDF]
These Smarandache spaces are right theories for objectives by logic. However, the mathematical combinatorics is a combinatorial theory for branches in classical mathematics motivated by a combinatorial speculation.
Linfan Mao, Mao. Linfan
core +1 more source
Slant submersions from almost paracontact Riemannian manifolds
In this paper, we introduce slant submersions from almost paracontact Riemannian manifoldsonto Riemannian manifolds. We give examples and investigate the geometry of foliationswhich are arisen from the definition of a Riemannian submersion.
YILMAZ GÜNDÜZALP
doaj
Sub-Riemannian geometry, Hamiltonian dynamics, micro-swimmers, copepod nauplii and copepod robot
The objective of this article is to present the seminal concepts and techniques of Sub-Riemannian geometry and Hamiltonian dynamics, complemented by adapted software to analyze the dynamics of the copepod micro-swimmer, where the model of swimming is the
Bernard Bonnard +3 more
doaj +1 more source
EvolvED: Evolutionary Embeddings to Understand the Generation Process of Diffusion Models
EvolvED visualises how diffusion models generate images by embedding intermediate outputs to preserve semantics and evolutionary structure. It supports analysis via (a) user‐defined goals and prompts, (b) sampling intermediate images, (c) extracting relevant features, and (d) visualising them in structured radial and rectilinear layouts for ...
Vidya Prasad +5 more
wiley +1 more source

