Already purchased this program?
Login to View
This video program is a part of the Premium package:
Multi-Motifgan (Mmgan): Motif-Targeted Graph Generation And Prediction
- IEEE MemberUS $11.00
- Society MemberUS $0.00
- IEEE Student MemberUS $11.00
- Non-IEEE MemberUS $15.00
Multi-Motifgan (Mmgan): Motif-Targeted Graph Generation And Prediction
Generative graph models create instances of graphs that mimic the properties of real-world networks. Generative models are successful at retaining pairwise associations in the underlying networks but often fail to capture higher-order connectivity pattern
Generative graph models create instances of graphs that mimic the properties of real-world networks. Generative models are successful at retaining pairwise associations in the underlying networks but often fail to capture higher-order connectivity pattern