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ORCIDEmanuele Rossi 0001
Person information
- affiliation: Sapienza University of Rome, Rome, Italy
- affiliation (Ph.D.): Imperial College London, London, UK
Other persons with the same name
- Emanuele Rossi — disambiguation page
- Emanuele Rossi 0002
![[0000-0002-2627-7468]](https://dblp.org/img/orcid-mark.12x12.png "0000-0002-2627-7468")
— Università degli Studi di Genova, Genova, Italy
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2020 – today
- 2026
[j2]Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros:
Training-Free Graph-Based Imputation of Missing Modalities in Multimodal Recommendation. IEEE Trans. Knowl. Data Eng. 38(5): 3250-3263 (2026)- [i19]Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros:
Training-free Graph-based Imputation of Missing Modalities in Multimodal Recommendation. CoRR abs/2602.17354 (2026) - [i18]Simone Antonelli, Vincent Davis, Harrison Rush, Anthony Potdevin, Jesse Shrader, Vikash Singh, Emanuele Rossi:
Predicting Channel Closures in the Lightning Network with Machine Learning. CoRR abs/2605.12759 (2026) - 2025
- [j1]Vikash Singh, Matthew Khanzadeh, Vincent Davis, Harrison Rush, Emanuele Rossi, Jesse Shrader, Pietro Lio':
Bayesian Binary Search. Algorithms 18(8): 452 (2025) - [i17]Emanuele Rossi:
Deep Learning on Real-World Graphs. CoRR abs/2510.21994 (2025) - 2024
- [c11]Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros:
Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation? CIKM 2024: 3943-3948 - [c10]Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany, Guillaume Rabusseau, Emanuele Rossi:
UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs. LoG 2024: 28 - [c9]Julia Gastinger, Shenyang Huang, Michael Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau:
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs. NeurIPS 2024 - [i16]Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Fragkiskos D. Malliaros, Tommaso Di Noia:
Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach. CoRR abs/2403.19841 (2024) - [i15]Julia Gastinger, Shenyang Huang, Mikhail Galkin, Erfan Loghmani, Ali Parviz, Farimah Poursafaei, Jacob Danovitch, Emanuele Rossi, Ioannis Koutis, Heiner Stuckenschmidt, Reihaneh Rabbany, Guillaume Rabusseau:
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs. CoRR abs/2406.09639 (2024) - [i14]Shenyang Huang, Farimah Poursafaei, Reihaneh Rabbany, Guillaume Rabusseau, Emanuele Rossi:
UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs. CoRR abs/2407.12269 (2024) - [i13]Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros:
Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation? CoRR abs/2408.11767 (2024) - [i12]Vikash Singh, Matthew Khanzadeh, Vincent Davis, Harrison Rush, Emanuele Rossi, Jesse Shrader, Pietro Lio:
Bayesian Binary Search. CoRR abs/2410.01771 (2024) - 2023
- [c8]Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli:
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. AAAI 2023: 9251-9259 - [c7]Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Yannick Hammerla, Michael M. Bronstein, Max Hansmire:
Graph Neural Networks for Link Prediction with Subgraph Sketching. ICLR 2023 - [c6]Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein:
Edge Directionality Improves Learning on Heterophilic Graphs. LoG 2023: 25 - [c5]Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. NeurIPS 2023 - [i11]Emanuele Rossi, Bertrand Charpentier, Francesco Di Giovanni, Fabrizio Frasca, Stephan Günnemann, Michael M. Bronstein:
Edge Directionality Improves Learning on Heterophilic Graphs. CoRR abs/2305.10498 (2023) - [i10]Shenyang Huang, Farimah Poursafaei, Jacob Danovitch, Matthias Fey, Weihua Hu, Emanuele Rossi, Jure Leskovec, Michael M. Bronstein, Guillaume Rabusseau, Reihaneh Rabbany:
Temporal Graph Benchmark for Machine Learning on Temporal Graphs. CoRR abs/2307.01026 (2023) - 2022
- [c4]Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong:
Learning to Infer Structures of Network Games. ICML 2022: 18809-18827 - [c3]Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs With Missing Node Features. LoG 2022: 11 - [i9]Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderón, Michael M. Bronstein, Marcello Restelli:
Provably Efficient Causal Model-Based Reinforcement Learning for Systematic Generalization. CoRR abs/2202.06545 (2022) - [i8]Emanuele Rossi, Federico Monti, Yan Leng, Michael M. Bronstein, Xiaowen Dong:
Learning to Infer Structures of Network Games. CoRR abs/2206.08119 (2022) - [i7]Benjamin Paul Chamberlain, Sergey Shirobokov, Emanuele Rossi, Fabrizio Frasca, Thomas Markovich, Nils Hammerla, Michael M. Bronstein, Max Hansmire:
Graph Neural Networks for Link Prediction with Subgraph Sketching. CoRR abs/2209.15486 (2022) - 2021
- [c2]Ben Chamberlain, James Rowbottom, Maria I. Gorinova, Michael M. Bronstein, Stefan Webb, Emanuele Rossi:
GRAND: Graph Neural Diffusion. ICML 2021: 1407-1418 - [i6]Benjamin Paul Chamberlain, James Rowbottom, Maria I. Gorinova, Stefan Webb, Emanuele Rossi, Michael M. Bronstein:
GRAND: Graph Neural Diffusion. CoRR abs/2106.10934 (2021) - [i5]Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein:
On the Unreasonable Effectiveness of Feature propagation in Learning on Graphs with Missing Node Features. CoRR abs/2111.12128 (2021) - 2020
- [c1]Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein:
Tuning Word2vec for Large Scale Recommendation Systems. RecSys 2020: 732-737 - [i4]Emanuele Rossi, Fabrizio Frasca, Ben Chamberlain, Davide Eynard, Michael M. Bronstein, Federico Monti:
SIGN: Scalable Inception Graph Neural Networks. CoRR abs/2004.11198 (2020) - [i3]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) - [i2]Benjamin Paul Chamberlain, Emanuele Rossi, Dan Shiebler, Suvash Sedhain, Michael M. Bronstein:
Tuning Word2vec for Large Scale Recommendation Systems. CoRR abs/2009.12192 (2020)
2010 – 2019
- 2019
- [i1]Emanuele Rossi, Federico Monti, Michael M. Bronstein, Pietro Liò:
ncRNA Classification with Graph Convolutional Networks. CoRR abs/1905.06515 (2019)
Coauthor Index
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last updated on 2026-06-10 23:08 CEST by the dblp team
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