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Found 6 papers, 4 papers with code
Reconstructing Graph Diffusion History from a Single Snapshot
They are exclusively based on the maximum likelihood estimation (MLE) formulation and require to know true diffusion parameters.
Networked Time Series Imputation via Position-aware Graph Enhanced Variational Autoencoders
First, we define the problem of imputation over NTS which contains missing values in both node time series features and graph structures.
MAD-VAE: Manifold Awareness Defense Variational Autoencoder
Our experiments also include attacks on the latent space of the defensive model.
Learning Interpretable Representation for Controllable Polyphonic Music Generation
While deep generative models have become the leading methods for algorithmic composition, it remains a challenging problem to control the generation process because the latent variables of most deep-learning models lack good interpretability.
Deep Music Analogy Via Latent Representation Disentanglement
Analogy-making is a key method for computer algorithms to generate both natural and creative music pieces.
