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ORCIDFederico Monti
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2020 – today
- 2023
[c11]Vanessa Cai, Pradeep Prabakar, Manuel Serrano Rebuelta, Lucas Rosen, Federico Monti, Katarzyna Janocha, Tomo Lazovich, Jeetu Raj, Yedendra Shrinivasan, Hao Li, Thomas Markovich:
TwERC: High Performance Ensembled Candidate Generation for Ads Recommendation at Twitter. AdKDD@KDD 2023- [i16]Vanessa Cai, Pradeep Prabakar, Manuel Serrano Rebuelta, Lucas Rosen, Federico Monti, Katarzyna Janocha, Tomo Lazovich, Jeetu Raj, Yedendra Shrinivasan, Hao Li, Thomas Markovich:
TwERC: High Performance Ensembled Candidate Generation for Ads Recommendation at Twitter. CoRR abs/2302.13915 (2023) - 2022
- [c10]Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong:
Learning to Infer Structures of Network Games. ICML 2022: 18809-18827 - [i15]Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong:
Learning to Infer Structures of Network Games. CoRR abs/2206.08119 (2022) - 2020
- [i14]Emanuele Rossi, Fabrizio Frasca, Ben Chamberlain, Davide Eynard, Michael M. Bronstein, Federico Monti:
SIGN: Scalable Inception Graph Neural Networks. CoRR abs/2004.11198 (2020) - [i13]Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, Davide Eynard, Federico Monti, Michael M. Bronstein:
Temporal Graph Networks for Deep Learning on Dynamic Graphs. CoRR abs/2006.10637 (2020)
2010 – 2019
- 2019
- [j2]Ron Levie
, Federico Monti, Xavier Bresson, Michael M. Bronstein:
CayleyNets: Graph Convolutional Neural Networks With Complex Rational Spectral Filters. IEEE Trans. Signal Process. 67(1): 97-109 (2019) - [c9]Michael M. Bronstein, Leonidas J. Guibas, Iasonas Kokkinos, Or Litany, Niloy J. Mitra, Federico Monti, Emanuele Rodolà:
Deep Learning for Computer Graphics and Geometry Processing. Eurographics (Tutorials) 2019: 43 - [c8]Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas J. Guibas:
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. ICLR (Poster) 2019 - [i12]Federico Monti, Fabrizio Frasca, Davide Eynard, Damon Mannion, Michael M. Bronstein:
Fake News Detection on Social Media using Geometric Deep Learning. CoRR abs/1902.06673 (2019) - [i11]Emanuele Rossi, Federico Monti, Michael M. Bronstein, Pietro Liò:
ncRNA Classification with Graph Convolutional Networks. CoRR abs/1905.06515 (2019) - 2018
- [c7]Federico Monti, Karl Otness, Michael M. Bronstein:
MOTIFNET: A Motif-Based Graph Convolutional Network for Directed Graphs. DSW 2018: 225-228 - [c6]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Deep Geometric Matrix Completion: A New Way for Recommender Systems. ICASSP 2018: 6852-6856 - [c5]Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna:
Graph Neural Networks for IceCube Signal Classification. ICMLA 2018: 386-391 - [i10]Federico Monti, Karl Otness, Michael M. Bronstein:
MotifNet: a motif-based Graph Convolutional Network for directed graphs. CoRR abs/1802.01572 (2018) - [i9]Jan Svoboda, Jonathan Masci, Federico Monti, Michael M. Bronstein, Leonidas J. Guibas:
PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks. CoRR abs/1806.00088 (2018) - [i8]Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, Michael M. Bronstein:
Dual-Primal Graph Convolutional Networks. CoRR abs/1806.00770 (2018) - [i7]Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna:
Graph Neural Networks for IceCube Signal Classification. CoRR abs/1809.06166 (2018) - [i6]Kevin McCloskey, Ankur Taly, Federico Monti, Michael P. Brenner, Lucy J. Colwell:
Using Attribution to Decode Dataset Bias in Neural Network Models for Chemistry. CoRR abs/1811.11310 (2018) - 2017
- [c4]Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein:
Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs. CVPR 2017: 5425-5434 - [c3]Jan Svoboda, Federico Monti, Michael M. Bronstein:
Generative convolutional networks for latent fingerprint reconstruction. IJCB 2017: 429-436 - [c2]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks. NIPS 2017: 3697-3707 - [i5]Federico Monti, Michael M. Bronstein, Xavier Bresson:
Geometric Matrix Completion with Recurrent Multi-Graph Neural Networks. CoRR abs/1704.06803 (2017) - [i4]Jan Svoboda, Federico Monti, Michael M. Bronstein:
Generative Convolutional Networks for Latent Fingerprint Reconstruction. CoRR abs/1705.01707 (2017) - [i3]Ron Levie, Federico Monti, Xavier Bresson, Michael M. Bronstein:
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters. CoRR abs/1705.07664 (2017) - 2016
- [j1]Denis Tomè, Federico Monti, Luca Baroffio, Luca Bondi, Marco Tagliasacchi, Stefano Tubaro:
Deep Convolutional Neural Networks for pedestrian detection. Signal Process. Image Commun. 47: 482-489 (2016) - [i2]Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda, Michael M. Bronstein:
Geometric deep learning on graphs and manifolds using mixture model CNNs. CoRR abs/1611.08402 (2016) - 2015
- [i1]Denis Tomè, Federico Monti, Luca Baroffio, Luca Bondi, Marco Tagliasacchi, Stefano Tubaro:
Deep convolutional neural networks for pedestrian detection. CoRR abs/1510.03608 (2015) - 2014
- [c1]Federico Monti, Susanna Reggiani, Gaetano Barone, Elena Gnani, Antonio Gnudi, Giorgio Baccarani, Stefano Poli, Ming-Yeh Chuang, Weidong Tian, Dhanoop Varghese, Rick Wise:
TCAD analysis of HCS degradation in LDMOS devices under AC stress conditions. ESSDERC 2014: 333-336
Coauthor Index
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