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The network structure can provide powerful insights when modeling social interactions.
The agent’s attribute table already encodes nodes and node features. Meanwhile, the Network DataFrame would encode the relationships between nodes along with the attributes of these relationships. This setup should also allow for compatibility with other spatial structures.
For PyTorch integration, Ibis offers a to_torch command that simplifies tensor conversion. Additionally, we could introduce a command to retrieve a tensor-based representation directly, making it possible to leverage libraries like PyTorch Geometric or DGL for advanced relational analysis.
The text was updated successfully, but these errors were encountered:
The network structure can provide powerful insights when modeling social interactions.
The agent’s attribute table already encodes nodes and node features. Meanwhile, the Network DataFrame would encode the relationships between nodes along with the attributes of these relationships. This setup should also allow for compatibility with other spatial structures.
For PyTorch integration, Ibis offers a to_torch command that simplifies tensor conversion. Additionally, we could introduce a command to retrieve a tensor-based representation directly, making it possible to leverage libraries like PyTorch Geometric or DGL for advanced relational analysis.
The text was updated successfully, but these errors were encountered: