Results 31 to 40 of about 122 (118)
Applied SciencesAutomated handwritten signature verification continues to pose significant challenges. A common approach for developing writer-independent signature verifiers involves the use of a dichotomizer, a function that generates a dissimilarity vector with the ...
Nikolaos Vasilakis +2 more
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A Simplified Algorithm for Inverting Higher Order Diffusion Tensors
Axioms, 2014 In Riemannian geometry, a distance function is determined by an inner product on the tangent space. In Riemann–Finsler geometry, this distance function can be determined by a norm.
Laura Astola +4 more
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Mathematical Methods in the Applied Sciences, Volume 48, Issue 6, Page 6912-6917, April 2025.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
A strictly local solution to the problem of energy in general relativity
Frontiers in Astronomy and Space SciencesThe problem of energy and its conservation is more than a century old in general relativity (GR) and is considered by many scholars to be, at least, not sufficiently solved.
Werner M. Vieira, Nadja S. Magalhaes
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Initial State Privacy of Nonlinear Systems on Riemannian Manifolds
International Journal of Robust and Nonlinear Control, EarlyView.ABSTRACT In this paper, we investigate initial state privacy protection for discrete‐time nonlinear closed systems. By capturing Riemannian geometric structures inherent in such privacy challenges, we refine the concept of differential privacy through the introduction of an initial state adjacency set based on Riemannian distances.
Le Liu, Yu Kawano, Antai Xie, Ming Cao
wiley +1 more source
A 4D geometric morphometrics workflow to quantify complex biological motion
Methods in Ecology and Evolution, EarlyView.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
Calibrating Bayesian inference
British Journal of Mathematical and Statistical Psychology, EarlyView.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
SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
Computer Graphics Forum, EarlyView.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
EvolvED: Evolutionary Embeddings to Understand the Generation Process of Diffusion Models
Computer Graphics Forum, EarlyView.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