marktechpost

Higher-Order Guided Diffusion for Graph Generation: A Coarse-to-Fine Approach to Preserving Topological Structures

Graph generation is a complex problem that involves constructing structured, non-Euclidean representations while maintaining meaningful relationships between entities. Most current methods fail to ...
GitHub

adjacency-matrix-graph

Add a description, image, and links to the adjacency-matrix-graph topic page so that developers can more easily learn about it.
Frontiers

Predicting microbe–disease association based on graph autoencoder and inductive matrix completion with multi-similarities fusion

1 College of Computer Science and Engineering, Guilin University of Technology, Guilin, China 2 Guangxi Key Laboratory of Embedded Technology and Intelligent Systems, Guilin University of Technology, ...
Scientific Research Publishing

Calvet, R.G. (2017) On Matrix Representations of Geometric (Clifford) Algebras. Journal of Geometry and Symmetry in Physics, 43, 1-36.

ABSTRACT: In this paper, from the spacetime algebra associated with the Minkowski space ℝ 3,1 by means of a change of signature, we describe a quaternionic representation of the split-tetraquaternion ...
C&EN

Physical Graph-Based Spatiotemporal Fusion Approach for Process Fault Diagnosis

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In this study, the synergies of GCN and LSTM are leveraged to ...
Frontiers

Classification of Multiple Sclerosis Clinical Profiles via Graph Convolutional Neural Networks

Recent advances in image acquisition and processing techniques, along with the success of novel deep learning architectures, have given the opportunity to develop innovative algorithms capable to ...