Quantum max-flow in the bridge graph [PDF]
Transformation Groups (advance online publication), 2024, 2022 The quantum max-flow quantifies the maximal possible entanglement between two regions of a tensor network state for a fixed graph and fixed bond dimensions. In this work, we calculate the quantum max-flow exactly in the case of the bridge graph. The result is achieved by drawing connections to the theory of prehomogenous tensor and the representation ...
Fulvio Gesmundo +2 more
arxiv +2 more sources
From Graph Theory to Graph Neural Networks (GNNs): The Opportunities of GNNs in Power Electronics
IEEE Access, 2023 Graph theory within power electronics, developed over a 50-year span, is continually evolving, necessitating ongoing research endeavors. Facing with the never-been-seen explosion of graph-structured data, the state-of-the-art deep learning technique ...
Yuzhuo Li +3 more
doaj +2 more sources
GT-DTW: Bridging Graph Theory and Dynamic Time Warping for Complex Time Series Analysis [PDF]
, 2023 <p>Classification of time series data plays a critical role across various domains, enabling pattern recognition and trend prediction. Traditional methods like Dynamic Time Warping (DTW) have been widely used to measure similarity between time series, but there are challenges related to computational complexity and sensitivity to noise.
Sachit Mahajan
+7 more sources
A Theoretical Analysis Of Nearest Neighbor Search On Approximate Near Neighbor Graph [PDF]
arXiv, 2023 Graph-based algorithms have demonstrated state-of-the-art performance in the nearest neighbor search (NN-Search) problem. These empirical successes urge the need for theoretical results that guarantee the search quality and efficiency of these algorithms. However, there exists a practice-to-theory gap in the graph-based NN-Search algorithms.
Anshumali Shrivastava +2 more
arxiv +3 more sources
Extending Undirected Graph Techniques to Directed Graphs via Category Theory
MathematicsWe use Category Theory to construct a ‘bridge’ relating directed graphs with undirected graphs, such that the notion of direction is preserved. Specifically, we provide an isomorphism between the category of simple directed graphs and a category we call ‘
Sebastian Pardo-Guerra +4 more
doaj +2 more sources
Localization–delocalization matrices: bridging QTAIM and chemical graph theory [PDF]
Acta Crystallographica Section A Foundations and Advances, 2017 Ismat Sumar +3 more
openaire +3 more sources
ETHNOMATHEMATICS: THE CONCEPT OF WEIGHTED GRAPHS IN THE TRADITIONAL GAME OF DAM [PDF]
Jurnal Magister Pendidikan MatematikaThis research integrates graph theory concepts with the traditional game of DAM originating from North Maluku, particularly in Ternate City. An ethnomathematics approach is employed to bridge mathematics education with the preservation of local culture ...
Bustan, Ariestha Widyastuty +3 more
core +4 more sources
Graph Theory Data for Topological Quantum Chemistry [PDF]
Physical Review E, 2017 Topological phases of noninteracting particles are distinguished by global properties of their band structure and eigenfunctions in momentum space.
Aroyo, M. I. +7 more
core +2 more sources
Graph Neural Networks Provably Benefit from Structural Information: A Feature Learning Perspective [PDF]
arXiv.org, 2023 Graph neural networks (GNNs) have pioneered advancements in graph representation learning, exhibiting superior feature learning and performance over multilayer perceptrons (MLPs) when handling graph inputs.
Cao, Xin +4 more
core +2 more sources
Uncertainty in Graph Neural Networks: A Survey
arXiv.orgGraph Neural Networks (GNNs) have been extensively used in various real-world applications. However, the predictive uncertainty of GNNs stemming from diverse sources such as inherent randomness in data and model training errors can lead to unstable and ...
Liu, Kay +5 more
core +2 more sources