Generalised implicit neural representations.
D. Grattarola, P. Vandergheynst.
Neural Information Processing Systems (NeurIPS 2022)
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Code
Learning graph cellular automata.
D. Grattarola, L. Livi, C. Alippi.
Neural Information Processing Systems (NeurIPS 2021)
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Code
Poster
Graph edit networks.
B. Paassen, D. Grattarola, D. Zambon, C. Alippi, B. Hammer.
International Conference on Learning Representations (ICLR 2021)
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Code
Spectral clustering with graph neural networks for graph pooling.
F. M. Bianchi*, D. Grattarola*, C. Alippi.
International Conference on Machine Learning (ICML 2020)
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Code (TF)
Code (Torch)
Autoregressive models for sequences of graphs.
D. Zambon*, D. Grattarola*, L. Livi, C. Alippi.
International Joint Conference on Neural Networks (IJCNN 2019)
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Code
DOI
Understanding pooling in graph neural networks.
D. Grattarola, D. Zambon, F. M. Bianchi, C. Alippi.
IEEE Transactions on Neural Networks and Learning Systems (2022)
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Code
DOI
Seizure localisation with attention-based graph neural networks.
D. Grattarola, L. Livi, C. Alippi, R. Wennberg, T. A. Valiante.
Expert Systems with Applications (2022)
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DOI
XENet: using a new graph convolution to accelerate the timeline for protein design on quantum computers.
J. B. Maguire, D. Grattarola, V. K. Mulligan, E. Klyshko, H. Melo.
PLOS Computational Biology (2021)
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Code
DOI
Graph neural networks in TensorFlow and Keras with Spektral.
D. Grattarola, C. Alippi.
Computational Intelligence Magazine (2020)
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Code
DOI
Hierarchical representation learning in graph neural networks with node decimation pooling.
F. M. Bianchi, D. Grattarola, L. Livi, C. Alippi.
IEEE Transactions on Neural Networks and Learning Systems (2020)
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Code
DOI
Graph neural networks with convolutional ARMA filters.
F. M. Bianchi, D. Grattarola, L. Livi, C. Alippi.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2021)
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Code (TF)
Code (Torch)
DOI
Adversarial autoencoders with constant-curvature latent manifolds.
D. Grattarola, L. Livi, C. Alippi.
Applied Soft Computing (2019)
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Code
DOI
Change detection in graph streams by learning graph embeddings on constant-curvature manifolds.
D. Grattarola, D. Zambon, L. Livi, C. Alippi.
IEEE Transactions on Neural Networks and Learning Systems (2019)
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Code
DOI
Content-based approaches for cold-start job recommendations.
M. Bianchi, F. Cesaro, F. Ciceri, M. Dagrada, A. Gasparin, D. Grattarola, I. Inajjar, A. M. Metelli, L. Cella.
Proceedings of the ACM Recsys Challenge (2017)
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DOI
