Publications

Glitch art #1 (by Daniele Grattarola)

Conference papers

Hierarchical neural cellular automata
R. Pande, D. Grattarola
Artificial Life Conference (ALife 2023)  |  Code  DOI 

Generalised implicit neural representations
D. Grattarola, P. Vandergheynst
Neural Information Processing Systems (NeurIPS 2022)  |  Code  Poster 

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

E(n)-equivariant graph neural cellular automata
G. Gala, D. Grattarola , E. Quaeghebeur
Transactions on Machine Learning Research (2024)  |  Code 

Unsupervised heterophilous network embedding via r-ego network discrimination
Z. Zhong, G. Gonzalez, D. Grattarola, J. Pang
Transactions on Machine Learning Research (2022)  |  Code 

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  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)  |  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 

Others

Performance and structural coverage of the latest, in-development AlphaFold model
Google DeepMind AlphaFold Team, Isomorphic Labs Team
Whitepaper (2023)

Graph neural networks: operators and architectures
D. Grattarola
PhD thesis (2021)

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 


* Equal contribution
As independent researcher