GRAPH ENERGY OF THE COPRIME GRAPH ON GENERALIZED QUATERNION GROUP
This paper investigates the Degree Square Sum Energy , Degree Exponent Energy , and Degree Exponent Sum Energy of the coprime graph on generalized quaternion group .
Miftahurrahman Miftahurrahman +3 more
doaj +1 more source
Parametrizing Del Pezzo surfaces of degree 8 using Lie algebras [PDF]
Willem A. de Graaf +2 more
openalex +1 more source
Cognitive Competence and Problem-Solving Involving 1st Degree Algebraic Equations
Yasmini Lais Spindler Sperafico +2 more
openalex +1 more source
Conditions for the Yoneda algebra of a local ring to be generated in low degrees [PDF]
Justin Hoffmeier, Liana M. Şega
openalex +2 more sources
On the degree of the polynomial defining a planar algebraic curves of constant width
In this paper, we consider a family of closed planar algebraic curves $\mathcal{C}$ which are given in parametrization form via a trigonometric polynomial $p$.
Bardet, Magali, Bayen, Térence
core +1 more source
Algebraic groups and small transcendence degree I
This paper contains many results on algebraic independence of transcendental numbers of the following form: in certain specified sets of numbers (connected with values of exponential or elliptic functions, for instance), at least two elements are algebraically independent. One of the most interesting features of this paper is that all these results are
openaire +2 more sources
Revealing Protein–Protein Interactions Using a Graph Theory‐Augmented Deep Learning Approach
This study presents a fast, cost‐efficient approach for classifying protein–protein interactions by integrating graph‐theory parametrization with deep learning (DL). Multiscale features extracted from graph‐encoded polarized‐light microscopy (PLM) images enable accurate prediction of binding strengths.
Bahar Dadfar +5 more
wiley +1 more source
Degree Bounds for Gröbner Bases in Algebras of Solvable Type [PDF]
Matthias Aschenbrenner, Anton Leykin
openalex +1 more source
Algebraic Points of Any Given Degree on the Affine Equation Curve <i>y</i><sup>11</sup>= <i>x</i><sup>4</sup>(<i>x</i> − 1)<sup>4</sup> [PDF]
Mouhamadou Diaby Gassama +2 more
openalex +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source

