Evolutionary game theory mathematically conceptualizes and analyzes biological interactions where one’s fitness not only depends on one’s own t
Awesome papers (codes) about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs) and their applications (i.e. Recommender Systems). Survey Papers 2025 Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding (WSDM, 2025) [paper][code] ...
For example, is the dynamic graph characterized by many large cliques which appear at fixed intervals of time, or perhaps by several large stars with dominant hubs that persist throughout? In this chapter we focus on these questions, and specifically on constructing concise summaries of large, ...
The graph structures consider incidence dynamic relationships of both inflows and outflows. Then we design a novel dynamic graph recurrent convolutional neural network model, namely Dynamic-GRCNN, to learn the spatial-temporal features representation for urban transportation network topological structures ...
Deep learning methods have also found applications in protein-related prediction. Their potent expressivity has proven increasingly pivotal in PPI site prediction in parallel with the exponential increase of biological data. For example, Zeng et al. [11] introduced DeepPPISP, a PPI site prediction ...
Most analysis has been done on static graph embedding. Recently, however, some works have been devoted to studying dynamic graph embedding. Motivating example We consider a toy example to motivate the idea of capturing network dynamics. Consider an evolution of graph G, G={G1,..,GT}, where...
To show how this graph could be created, the following example uses node A, a kernel upstream of the conditional node, B, to set the value of the conditional based on the results of work done by that kernel. The body of the conditional is populated using the graph API. ...
Here's an example of a rule that uses an extension attribute as a property: (user.extensionAttribute15 -eq "Marketing") Custom extension propertiescan be synced from on-premises Windows Server Active Directory, from a connected SaaS application, or created using Microsoft Graph, and are of the...
graph neural network only considers static spatial information. For example, GraphSAGE (Hamilton, Ying, and Leskovec 2017)21defines fixed neighbors and aggregates each node's neighborhood and own attributes. Wu et al.22proposed a graph-wave network that uses extended one-dimensional convolution to ...
35is such a knowledge graph that aims to encompass all aspects of scientific research laboratories as shown in Fig.1a in their entirety: The experiment itself, including its physical setup and underlying chemistry; moving handlers that can be of human or robotic nature; and the laboratory ...