The variational graph autoencoder (VGAE) regularizes its posterior toward the prior with the Kullback-Leibler divergence, a choice inherited from the variational autoencoder rather than argued for. We introduce the generalized graph variational autoencoder (GGVA), which replaces that term with any member of the R\'enyi...
Kleyton da Costa, Bernardo Modenesi, I. Menezes et al.· 0 citations
LTGA is a graph attention layer whose Tsallis entropic index $q$ is learned jointly with the weights, interpolating continuously between heavy-tailed, softmax, compact-support and compact-support attention at four granularities from a global scalar to a per-edge index, under a bounded reparameterization that starts eve...
Behavioral topology is shaped more by the deployment harness than by the LLM, providing a model-agnostic structural primitive for safety auditing and runtime monitoring, and addresses both prediction goals.
Seonglae Cho, F. Fernandez, Umar Mohammed et al.· 4 citations· ⚡1
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