Emanuele Rossi
Emanuele Rossi
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Geciteerd door
Geciteerd door
Temporal Graph Networks for Deep Learning on Dynamic Graphs
E Rossi, B Chamberlain, F Frasca, D Eynard, F Monti, M Bronstein
ICML 2020 Workshop on Graph Representation Learning, 2020
SIGN: Scalable Inception Graph Neural Networks
E Rossi, F Frasca, B Chamberlain, D Eynard, M Bronstein, F Monti
ICML 2020 Workshop on Graph Representation Learning, 2020
Grand: Graph neural diffusion
B Chamberlain, J Rowbottom, MI Gorinova, M Bronstein, S Webb, E Rossi
International Conference on Machine Learning (ICML 2021), 1407-1418, 2021
On the unreasonable effectiveness of feature propagation in learning on graphs with missing node features
E Rossi, H Kenlay, MI Gorinova, BP Chamberlain, X Dong, M Bronstein
Learning on Graphs Conference (LoG) 2022, 2021
Graph Neural Networks for Link Prediction with Subgraph Sketching
BP Chamberlain, S Shirobokov, E Rossi, F Frasca, T Markovich, ...
International Conference on Learning Representations (ICLR) 2022, 2022
Tuning word2vec for large scale recommendation systems
BP Chamberlain, E Rossi, D Shiebler, S Sedhain, MM Bronstein
Proceedings of the 14th ACM Conference on Recommender Systems, 732-737, 2020
Temporal Graph Benchmark for Machine Learning on Temporal Graphs
S Huang, F Poursafaei, J Danovitch, M Fey, W Hu, E Rossi, J Leskovec, ...
NeurIPS 2023 Datasets and Benchmarks Track, 2023
ncRNA Classification with Graph Convolutional Networks
E Rossi, F Monti, M Bronstein, P Li˛
KDD 2019 Workshop on Deep Learning on Graphs, 2019
Edge Directionality Improves Learning on Heterophilic Graphs
E Rossi, B Charpentier, F Di Giovanni, F Frasca, S GŘnnemann, ...
Learning on Graphs Conference (LoG) 2023, 2023
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization
M Mutti, R De Santi, E Rossi, JF Calderon, M Bronstein, M Restelli
Proceedings of the AAAI Conference on Artificial Intelligence 2022, 2022
Learning to Infer Structures of Network Games
E Rossi, F Monti, Y Leng, MM Bronstein, X Dong
International Conference on Machine Learning (ICML 2022), 2022
Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach
D Malitesta, E Rossi, C Pomo, FD Malliaros, T Di Noia
arXiv preprint arXiv:2403.19841, 2024
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