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Code for my ICML 2019 paper "Correlated Variational Auto-Encoders"
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src Added the preprocessing code for the Epinions dataset. Aug 20, 2019
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README.md Update README.md Aug 20, 2019

README.md

Correlate-Variational-Auto-Encoders

Code for my ICML 2019 paper Correlated Variational Auto-Encoders

Files

  • cvae_ind.py: Code for the algorithm CVAEind on general graphs (Section 4.2.3).
  • cvae_corr.py: Code for the algorithm CVAEcorr on general graphs (Section 4.2.3).
  • process_tree_data.py: Code for constructing the synthetic dataset for the spectral clustering experiment (Section 4.2.2).
  • process_Epinions_data.py: Code for preprocessing the Epinions dataset for the general graph link prediction experiment (Section 4.2.3). To use this code, construct an NumPy npz file that contains two arrays with values from the two datasets (ratings_data and trust_data) on the Epinions dataset website [1] and run this code with the argument input_data_file_name being set as the npz file directory.

References

[1] Trust-aware recommender systems. P Massa, P Avesani. Proceedings of the 2007 ACM conference on Recommender systems, 17-24

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