2024
Learning Latent Structures in Network Games via Data-Dependent Gated-Prior Graph Variational Autoencoders
ICML 2024poster
In network games, individuals interact strategically within network environments to maximize their utilities. However, obtaining network structures is challenging. In this work, we propose an unsupervised learning model, called data-dependent gated-prior graph variational autoencoder (GPGVAE), that…