Publications

Conference papers

Learning graph cellular automata.
D. Grattarola, L. Livi, C. Alippi.
Neural Information Processing Systems (NeurIPS 2021)  |  Code  Poster 

Graph edit networks.
B. Paassen, D. Grattarola, D. Zambon, C. Alippi, B. Hammer.
International Conference on Learning Representations (ICLR 2021)  |  Code 

Spectral clustering with graph neural networks for graph pooling.
F. M. Bianchi*, D. Grattarola*, C. Alippi.
International Conference on Machine Learning (ICML 2020)  |  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)  |  Code  DOI 

Journal papers

Understanding pooling in graph neural networks.
D. Grattarola, D. Zambon, F. M. Bianchi, C. Alippi.
IEEE Transactions on Neural Networks and Learning Systems (2022)  |  Code 

Seizure localisation with attention-based graph neural networks.
D. Grattarola, L. Livi, C. Alippi, R. Wennberg, T. A. Valiante.
Expert Systems with Applications (2022)  |  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)  |  Code  DOI 

Graph neural networks in TensorFlow and Keras with Spektral.
D. Grattarola, C. Alippi.
Computational Intelligence Magazine (2020)  |  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)  |  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)  |  Code (TF)  Code (Torch)  DOI 

Adversarial autoencoders with constant-curvature latent manifolds.
D. Grattarola, L. Livi, C. Alippi.
Applied Soft Computing (2019)  |  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)  |  Code  DOI 

Preprints

Generalised implicit neural representations.
D. Grattarola, P. Vandergheynst.
Preprint (2022)  |  Code 

Unsupervised heterophilous network embedding via r-ego network discrimination.
Z. Zhong, G. Gonzalez, D. Grattarola, J. Pang.
Preprint (2022)

Others

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)  |  DOI 

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* Equal contribution