Federico Monti

发表

Dual-Primal Graph Convolutional Networks pdf

Stephan Günnemann, Michael M. Bronstein, Aleksandar Bojchevski, 2018, ArXiv.

Fake News Detection on Social Media using Geometric Deep Learning pdf

Davide Eynard, Michael M. Bronstein, Fabrizio Frasca, 2019, ArXiv.

Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs

Jonathan Masci, Michael M. Bronstein, Jan Svoboda, 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

Xavier Bresson, Michael M. Bronstein, Federico Monti, 2017, NIPS.

Temporal Graph Networks for Deep Learning on Dynamic Graphs pdf

Davide Eynard, Fabrizio Frasca, Michael Bronstein, 2020, ArXiv.

Deep Learning for Computer Graphics and Geometry Processing

Iasonas Kokkinos, Leonidas J. Guibas, Niloy J. Mitra, 2019, Eurographics.

Learning to Infer Structures of Network Games

Federico Monti, Xiaowen Dong, Yan Leng, 2022, ICML.

Global-Local Graph Neural Networks for Node-Classification

Wojciech Zaremba, Joan Bruna, M. Bronstein, 2022 .

CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters

Xavier Bresson, Michael M. Bronstein, Ron Levie, 2017, IEEE Transactions on Signal Processing.

SIGN: Scalable Inception Graph Neural Networks pdf

Davide Eynard, Fabrizio Frasca, Michael Bronstein, 2020, ArXiv.

ncRNA Classification with Graph Convolutional Networks pdf

Pietro Liò, Michael M. Bronstein, Emanuele Rossi, 2019, ArXiv.

PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks pdf

Leonidas J. Guibas, Jonathan Masci, Michael M. Bronstein, 2018, ICLR.

Interaction data are identifiable even across long periods of time

Y. de Montjoye, Federico Monti, Xiaowen Dong, 2022, Nature Communications.

Temporal Graph Networks for Deep Learning on Dynamic Graphs pdf

Davide Eynard, Fabrizio Frasca, Michael Bronstein, 2020, ArXiv.

Using attribution to decode binding mechanism in neural network models for chemistry

Ankur Taly, Lucy J. Colwell, Michael P. Brenner, 2018, Proceedings of the National Academy of Sciences.

Graph Neural Networks for IceCube Signal Classification

Prabhat, Joan Bruna, Zahra Ronaghi, 2018, 2018 17th IEEE International Conference on Machine Learning and Applications (ICMLA).

MOTIFNET: A MOTIF-BASED GRAPH CONVOLUTIONAL NETWORK FOR DIRECTED GRAPHS

Michael M. Bronstein, Federico Monti, Karl Otness, 2018, 2018 IEEE Data Science Workshop (DSW).

Deep Convolutional Neural Networks for pedestrian detection

Stefano Tubaro, Marco Tagliasacchi, Luca Bondi, 2015, Signal Process. Image Commun..

Generative convolutional networks for latent fingerprint reconstruction

Michael M. Bronstein, Jan Svoboda, Federico Monti, 2017, 2017 IEEE International Joint Conference on Biometrics (IJCB).

PEDESTRIAN DETECTION AND TRACKING IN LOW QUALITY IMAGES WITH DEEP NEURAL NETWORKS

Federico Monti, Federico Monti, 2015 .

Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks

M. Bronstein, X. Bresson, Federico Monti, 2017, NIPS.

Deep Geometric Matrix Completion: A New Way for Recommender Systems

Xavier Bresson, Michael M. Bronstein, Federico Monti, 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

CAYLEYNETS: SPECTRAL GRAPH CNNS WITH COMPLEX RATIONAL FILTERS

Xavier Bresson, Michael M. Bronstein, Ron Levie, 2018 .

TwERC: High Performance Ensembled Candidate Generation for Ads Recommendation at Twitter

Hao Li, Federico Monti, T. Lazovich, 2023, ArXiv.

Using attribution to decode binding mechanism in neural network models for chemistry

Lucy J. Colwell, M. Brenner, Federico Monti, 2018, Proceedings of the National Academy of Sciences.