Graph Neural Networks (GNNs) are used for graph data processing across various domains. Centralized training of GNNs often faces challenges due to privacy and regulatory issues, making federated ...

In light of the growing emphasis on the right to be forgotten of graph data, machine unlearning has been extended to unlearn the graph structures’ knowledge from graph neural networks (GNNs), namely, ...

Our proposed framework (Figure 1) embeds protein sequences using ESM-2 and converts predicted structures into Node2Vec-encoded contact graphs. (24) These representations are processed via dual ...