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Found 5 papers, 3 papers with code
Similarity of Neural Network Models: A Survey of Functional and Representational Measures
Measuring similarity of neural networks to understand and improve their behavior has become an issue of great importance and research interest.
Properties of Group Fairness Metrics for Rankings
By virtue of their diverse application contexts, we argue that such a comparative analysis is not straightforward.
A Comparative Evaluation of Quantification Methods
More generally, we find that the performance on multiclass quantification is inferior to the results obtained in the binary setting.
The Effects of Randomness on the Stability of Node Embeddings
We systematically evaluate the (in-)stability of state-of-the-art node embedding algorithms due to randomness, i. e., the random variation of their outcomes given identical algorithms and graphs.
Privacy Attacks on Network Embeddings
In that setting, we analyze whether after the removal of the node from the network and the deletion of the vector representation of the respective node in the embedding significant information about the link structure of the removed node is still encoded in the embedding vectors of the remaining nodes.
