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Generating graph-structured data requires learning the underlying distribution of graphs.
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Brenda, the enzyme database: updates and major new developments
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Zinc: a free tool to discover chemistry for biology
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Molgan: An implicit generative model for small molecular graphs
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Junction tree variational autoencoder for molecular graph generation
Jin, W., Barzilay, R., and Jaakkola, T · 2018
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Constrained generation of semantically valid graphs via regularizing variational autoencoders
Ma, T., Chen, J., and Xiao, C · 2018
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Fréchet chemnet distance: a metric for generative models for molecules in drug discovery
Preuer, K., Renz, P., Unterthiner, T., Hochreiter, S., and Klambauer, G · 2018
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Graphvae: Towards generation of small graphs using variational autoencoders
Simonovsky, M. and Komodakis, N · 2018
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Wang, H., Wang, J., Wang, J., Zhao, M., Zhang, W., Zhang, F., Xie, X., and Guo, M · 2018
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Generative code modeling with graphs
Brockschmidt, M., Allamanis, M., Gaunt, A. L., and Polozov, O · 2019
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Graphite: Iterative generative modeling of graphs
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Universal invariant and equivariant graph neural networks
Keriven, N. and Peyré, G · 2019
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Efficient graph generation with graph recurrent attention networks
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Permutation invariant graph generation via score-based generative modeling
Niu, C., Song, Y., Song, J., Zhao, S., Grover, A., and Ermon, S · 2020
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Graphaf: a flow-based autoregressive model for molecular graph generation
Shi, C., Xu, M., Zhu, Z., Zhang, W., Zhang, M., and Tang, J · 2020
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Improved techniques for training score-based generative models
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Moflow: an invertible flow model for generating molecular graphs
Zang, C. and Wang, F · 2020
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Accurate learning of graph representations with graph multiset pooling
Baek, J., Kang, M., and Hwang, S. J · 2021
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Wavegrad: Estimating gradients for waveform generation
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Graph normalizing flows
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Applied Stochastic Differential Equations
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Evaluation metrics for graph generative models: Problems, pitfalls, and practical solutions
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Score-based generative modeling in latent space
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