| Geometric deep learning on graphs and manifolds using mixture model CNNs MMB Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan ... arXiv preprint arXiv:1611.08402, 2016 | 2385* | 2016 |
| Cayleynets: Graph convolutional neural networks with complex rational spectral filters R Levie, F Monti, X Bresson, MM Bronstein IEEE Transactions on Signal Processing 67 (1), 97-109, 2018 | 860 | 2018 |
| Temporal graph networks for deep learning on dynamic graphs E Rossi, B Chamberlain, F Frasca, D Eynard, F Monti, M Bronstein arXiv preprint arXiv:2006.10637, 2020 | 839 | 2020 |
| Fake news detection on social media using geometric deep learning F Monti, F Frasca, D Eynard, D Mannion, MM Bronstein arXiv preprint arXiv:1902.06673, 2019 | 731 | 2019 |
| Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning P Gainza, F Sverrisson, F Monti, E Rodola, D Boscaini, MM Bronstein, ... Nature Methods 17 (2), 184-192, 2020 | 717 | 2020 |
| Geometric matrix completion with recurrent multi-graph neural networks F Monti, M Bronstein, X Bresson Advances in neural information processing systems 30, 2017 | 695 | 2017 |
| Deep convolutional neural networks for pedestrian detection D Tomè, F Monti, L Baroffio, L Bondi, M Tagliasacchi, S Tubaro Signal processing: image communication 47, 482-489, 2016 | 289 | 2016 |
| Sign: Scalable inception graph neural networks F Frasca, E Rossi, D Eynard, B Chamberlain, M Bronstein, F Monti arXiv preprint arXiv:2004.11198, 2020 | 281 | 2020 |
| Sign: Scalable inception graph neural networks E Rossi, F Frasca, B Chamberlain, D Eynard, M Bronstein, F Monti arXiv preprint arXiv:2004.11198 7, 15, 2020 | 190 | 2020 |
| Motifnet: a motif-based graph convolutional network for directed graphs F Monti, K Otness, MM Bronstein 2018 IEEE data science workshop (DSW), 225-228, 2018 | 174 | 2018 |
| Using attribution to decode binding mechanism in neural network models for chemistry K McCloskey, A Taly, F Monti, MP Brenner, LJ Colwell Proceedings of the National Academy of Sciences 116 (24), 11624-11629, 2019 | 111 | 2019 |
| Graph neural networks for icecube signal classification N Choma, F Monti, L Gerhardt, T Palczewski, Z Ronaghi, P Prabhat, ... 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 92 | 2018 |
| Dual-primal graph convolutional networks F Monti, O Shchur, A Bojchevski, O Litany, S Günnemann, MM Bronstein arXiv preprint arXiv:1806.00770, 2018 | 78 | 2018 |
| Communication, cognitive development and behavior in children with Cornelia de Lange Syndrome (CdLS): preliminary results PF Ajmone, C Rigamonti, F Dall'Ara, F Monti, P Vizziello, D Milani, ... American Journal of Medical Genetics Part B: Neuropsychiatric Genetics 165 …, 2014 | 54 | 2014 |
| Generative convolutional networks for latent fingerprint reconstruction J Svoboda, F Monti, MM Bronstein 2017 IEEE International joint conference on biometrics (IJCB), 429-436, 2017 | 49 | 2017 |
| Peernets: Exploiting peer wisdom against adversarial attacks J Svoboda, J Masci, F Monti, MM Bronstein, L Guibas arXiv preprint arXiv:1806.00088, 2018 | 42 | 2018 |
| Early manifestations in a cohort of children prenatally diagnosed with 47, XYY. Role of multidisciplinary counseling for parental guidance and prevention of aggressive behavior F Lalatta, E Folliero, U Cavallari, M Di Segni, B Gentilin, R Fogliani, ... Italian journal of pediatrics 38, 1-8, 2012 | 30 | 2012 |
| Ratiometric sweat secretion optical test in cystic fibrosis, carriers and healthy subjects G Bergamini, G Tridello, E Calcaterra, S Ceri, M Tagliasacchi, F Bianchi, ... Journal of Cystic Fibrosis 17 (2), 186-189, 2018 | 29 | 2018 |
| Interaction data are identifiable even across long periods of time AM Creţu, F Monti, S Marrone, X Dong, M Bronstein, YA de Montjoye Nature Communications 13 (1), 313, 2022 | 28 | 2022 |
| ncRNA classification with graph convolutional networks E Rossi, F Monti, M Bronstein, P Liò arXiv preprint arXiv:1905.06515, 2019 | 26 | 2019 |