Fragkiskos D. Malliaros

106 papers A* 6A 13B 7Misc 2Journal 61Unranked 14
YearRankTypeTitle / Venue / Authors
2026 J jnl
Training-Free Graph-Based Imputation of Missing Modalities in Multimodal Recommendation.
IEEE Trans. Knowl. Data Eng.
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros
2026 J jnl
Training-free Graph-based Imputation of Missing Modalities in Multimodal Recommendation.
CoRR
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros
2025 J jnl
A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning.
CoRR
Amadou S. Sangare, Nicolas Dunou, Jhony H. Giraldo, Fragkiskos D. Malliaros
2025 J jnl
A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning.
Trans. Mach. Learn. Res.
Amadou S. Sangare, Nicolas Dunou, Jhony H. Giraldo, Fragkiskos D. Malliaros
2025 A conf
ADMP-GNN: Adaptive Depth Message Passing GNN.
CIKM
Yassine Abbahaddou, Fragkiskos D. Malliaros, Johannes F. Lutzeyer, Michalis Vazirgiannis
2025 J jnl
ADMP-GNN: Adaptive Depth Message Passing GNN.
CoRR
Yassine Abbahaddou, Fragkiskos D. Malliaros, Johannes F. Lutzeyer, Michalis Vazirgiannis
2025 J jnl
COSMOS: Continuous Simplicial Neural Networks.
CoRR
Aref Einizade, Dorina Thanou, Fragkiskos D. Malliaros, Jhony H. Giraldo
2025 J jnl
Cometh: A continuous-time discrete-state graph diffusion model.
Trans. Mach. Learn. Res.
Antoine Siraudin, Fragkiskos D. Malliaros, Christopher Morris
2025 A conf
Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks.
CIKM
Hugo Attali, Thomas Papastergiou, Nathalie Pernelle, Fragkiskos D. Malliaros
2025 J jnl
Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks.
CoRR
Hugo Attali, Thomas Papastergiou, Nathalie Pernelle, Fragkiskos D. Malliaros
2025 J jnl
FAROS: Fair Graph Generation via Attribute Switching Mechanisms.
CoRR
Abdennacer Badaoui, Oussama Kharouiche, Hatim Mrabet, Daniele Malitesta, Fragkiskos D. Malliaros
2025 A* conf
Graph Neural Network Generalization With Gaussian Mixture Model Based Augmentation.
ICML
Yassine Abbahaddou, Fragkiskos D. Malliaros, Johannes F. Lutzeyer, Amine Mohamed Aboussalah, Michalis Vazirgiannis
2025 J jnl
Higher-Order GNNs Meet Efficiency: Sparse Sobolev Graph Neural Networks.
IEEE Trans. Signal Inf. Process. over Networks
Jhony H. Giraldo, Aref Einizade, Andjela Todorovic, Jhon A. Castro-Correa, Mohsen Badiey, Thierry Bouwmans, Fragkiskos D. Malliaros
2025 A conf
How Fair is Your Diffusion Recommender Model?
RecSys
Daniele Malitesta, Giacomo Medda, Erasmo Purificato, Mirko Marras, Fragkiskos D. Malliaros, Ludovico Boratto
2025 J jnl
Piecewise Constant Spectral Graph Neural Network.
CoRR
Vahan Martirosyan, Jhony H. Giraldo, Fragkiskos D. Malliaros
2025 J jnl
Piecewise Constant Spectral Graph Neural Network.
Trans. Mach. Learn. Res.
Vahan Martirosyan, Jhony H. Giraldo, Fragkiskos D. Malliaros
2025 J jnl
Retrieval-Constrained Decoding Reveals Underestimated Parametric Knowledge in Language Models.
CoRR
Rajaa El Hamdani, Samy Haffoudhi, Nils Holzenberger, Fabian M. Suchanek, Thomas Bonald, Fragkiskos D. Malliaros
2025 J jnl
Second-Order Tensorial Partial Differential Equations on Graphs.
CoRR
Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo
2025 — ed.
Trends and Applications in Knowledge Discovery and Data Mining - PAKDD 2025 Workshops, ADUR, FairPC, GLFM, PM4B and RAFDA, Sydney, NSW, Australia, June 10-13, 2025, Proceedings
PAKDD (Workshops)
Shuhan Yuan, Fragkiskos D. Malliaros, Xin Zheng
2024 — book
A Machine Learning Tour in Network Science.
Fragkiskos D. Malliaros
2024 J jnl
Centrality Graph Shift Operators for Graph Neural Networks.
CoRR
Yassine Abbahaddou, Fragkiskos D. Malliaros, Johannes F. Lutzeyer, Michalis Vazirgiannis
2024 J jnl
Cometh: A continuous-time discrete-state graph diffusion model.
CoRR
Antoine Siraudin, Fragkiskos D. Malliaros, Christopher Morris
2024 A* conf
Continuous Product Graph Neural Networks.
NeurIPS
Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo
2024 J jnl
Continuous Product Graph Neural Networks.
CoRR
Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo
2024 J jnl
Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach.
CoRR
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Fragkiskos D. Malliaros, Tommaso Di Noia
2024 A conf
Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?
CIKM
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros
2024 J jnl
Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?
CoRR
Daniele Malitesta, Emanuele Rossi, Claudio Pomo, Tommaso Di Noia, Fragkiskos D. Malliaros
2024 J jnl
Estimation of a causal directed acyclic graph process using non-gaussianity.
Digit. Signal Process.
Aref Einizade, Jhony H. Giraldo, Fragkiskos D. Malliaros, Sepideh Hajipour Sardouie
2024 J jnl
Gaussian Mixture Models Based Augmentation Enhances GNN Generalization.
CoRR
Yassine Abbahaddou, Fragkiskos D. Malliaros, Johannes F. Lutzeyer, Amine Mohamed Aboussalah, Michalis Vazirgiannis
2024 J jnl
Gegenbauer Graph Neural Networks for Time-Varying Signal Reconstruction.
IEEE Trans. Neural Networks Learn. Syst.
Jhon A. Castro-Correa, Jhony H. Giraldo, Mohsen Badiey, Fragkiskos D. Malliaros
2024 J jnl
Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction.
CoRR
Jhon A. Castro-Correa, Jhony H. Giraldo, Mohsen Badiey, Fragkiskos D. Malliaros
2024 J jnl
Graph Neural Networks for Treatment Effect Prediction.
CoRR
George Panagopoulos, Daniele Malitesta, Fragkiskos D. Malliaros, Jun Pang
2024 J jnl
Higher-Order GNNs Meet Efficiency: Sparse Sobolev Graph Neural Networks.
CoRR
Jhony H. Giraldo, Aref Einizade, Andjela Todorovic, Jhon A. Castro-Correa, Mohsen Badiey, Thierry Bouwmans, Fragkiskos D. Malliaros
2024 J jnl
How Fair is Your Diffusion Recommender Model?
CoRR
Daniele Malitesta, Giacomo Medda, Erasmo Purificato, Ludovico Boratto, Fragkiskos D. Malliaros, Mirko Marras, Ernesto William De Luca
2024 J jnl
Improving Molecular Modeling with Geometric GNNs: an Empirical Study.
CoRR
Ali Ramlaoui, Théo Saulus, Basile Terver, Victor Schmidt, David Rolnick, Fragkiskos D. Malliaros, Alexandre Duval
2024 J jnl
Learning graph representations for influence maximization.
Soc. Netw. Anal. Min.
George Panagopoulos, Nikolaos Tziortziotis, Michalis Vazirgiannis, Jun Pang, Fragkiskos D. Malliaros
2024 J jnl
Post-Hoc Robustness Enhancement in Graph Neural Networks with Conditional Random Fields.
CoRR
Yassine Abbahaddou, Sofiane Ennadir, Johannes F. Lutzeyer, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2024 J jnl
Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks.
CoRR
Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo
2024 A conf
The Factuality of Large Language Models in the Legal Domain.
CIKM
Rajaa El Hamdani, Thomas Bonald, Fragkiskos D. Malliaros, Nils Holzenberger, Fabian M. Suchanek
2024 J jnl
The Factuality of Large Language Models in the Legal Domain.
CoRR
Rajaa El Hamdani, Thomas Bonald, Fragkiskos D. Malliaros, Nils Holzenberger, Fabian M. Suchanek
2024 — conf
Uplift Modeling Under Limited Supervision.
ECML/PKDD (6)
George Panagopoulos, Daniele Malitesta, Fragkiskos D. Malliaros, Jun Pang
2023 J jnl
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems.
CoRR
Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein
2023 A* conf
FAENet: Frame Averaging Equivariant GNN for Materials Modeling.
ICML
Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
2023 J jnl
FAENet: Frame Averaging Equivariant GNN for Materials Modeling.
CoRR
Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
2023 Misc conf
Higher-Order Sparse Convolutions in Graph Neural Networks.
ICASSP
Jhony H. Giraldo, Sajid Javed, Arif Mahmood, Fragkiskos D. Malliaros, Thierry Bouwmans
2023 J jnl
Higher-order Sparse Convolutions in Graph Neural Networks.
CoRR
Jhony H. Giraldo, Sajid Javed, Arif Mahmood, Fragkiskos D. Malliaros, Thierry Bouwmans
2023 B conf
Maximizing Influence with Graph Neural Networks.
ASONAM
George Panagopoulos, Nikolaos Tziortziotis, Michalis Vazirgiannis, Fragkiskos D. Malliaros
2023 J jnl
Multiple Kernel Representation Learning on Networks.
IEEE Trans. Knowl. Data Eng.
Abdulkadir Çelikkanat, Yanning Shen, Fragkiskos D. Malliaros
2023 A conf
On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks.
CIKM
Jhony H. Giraldo, Konstantinos Skianis, Thierry Bouwmans, Fragkiskos D. Malliaros
2023 Misc conf
Time-Varying Signals Recovery Via Graph Neural Networks.
ICASSP
Jhon A. Castro-Correa, Jhony H. Giraldo, Anindya Mondal, Mohsen Badiey, Thierry Bouwmans, Fragkiskos D. Malliaros
2023 J jnl
Time-varying Signals Recovery via Graph Neural Networks.
CoRR
Jhon A. Castro-Correa, Jhony H. Giraldo, Anindya Mondal, Mohsen Badiey, Thierry Bouwmans, Fragkiskos D. Malliaros
2022 J jnl
BRANEnet: embedding multilayer networks for omics data integration.
BMC Bioinform.
Surabhi Jagtap, Aurélie Pirayre, Frédérique Bidard, Laurent Duval, Fragkiskos D. Malliaros
2022 J jnl
BraneMF: integration of biological networks for functional analysis of proteins.
Bioinform.
Surabhi Jagtap, Abdulkadir Çelikkanat, Aurélie Pirayre, Frédérique Bidard, Laurent Duval, Fragkiskos D. Malliaros
2022 A conf
Higher-order Clustering and Pooling for Graph Neural Networks.
CIKM
Alexandre Duval, Fragkiskos D. Malliaros
2022 J jnl
Higher-order Clustering and Pooling for Graph Neural Networks.
CoRR
Alexandre Duval, Fragkiskos D. Malliaros
2022 J jnl
Multi-Task Learning for Influence Estimation and Maximization.
IEEE Trans. Knowl. Data Eng.
George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2022 J jnl
Multiple Similarity Drug-Target Interaction Prediction with Random Walks and Matrix Factorization.
CoRR
Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros, Grigorios Tsoumakas, Apostolos N. Papadopoulos
2022 J jnl
Multiple similarity drug-target interaction prediction with random walks and matrix factorization.
Briefings Bioinform.
Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros, Grigorios Tsoumakas, Apostolos N. Papadopoulos
2022 B conf
NodeSig: Binary Node Embeddings via Random Walk Diffusion.
ASONAM
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros, Apostolos N. Papadopoulos
2022 J jnl
Understanding the Relationship between Over-smoothing and Over-squashing in Graph Neural Networks.
CoRR
Jhony H. Giraldo, Fragkiskos D. Malliaros, Thierry Bouwmans
2021 — conf
An Adversarial Attacker for Neural Networks in Regression Problems.
AISafety@IJCAI
Kavya Gupta, Jean-Christophe Pesquet, Béatrice Pesquet-Popescu, Fateh Kaakai, Fragkiskos D. Malliaros
2021 — conf
GraphSVX: Shapley Value Explanations for Graph Neural Networks.
ECML/PKDD (2)
Alexandre Duval, Fragkiskos D. Malliaros
2021 J jnl
GraphSVX: Shapley Value Explanations for Graph Neural Networks.
CoRR
Alexandre Duval, Fragkiskos D. Malliaros
2021 B conf
Influence Learning and Maximization.
ICWE
George Panagopoulos, Fragkiskos D. Malliaros
2021 J jnl
Learning to Maximize Influence.
CoRR
George Panagopoulos, Nikolaos Tziortziotis, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2021 — conf
Multiomics Data Integration for Gene Regulatory Network Inference with Exponential Family Embeddings.
EUSIPCO
Surabhi Jaatan, Abdulkadir Çelikkanat, Aurelic Piravre, Frédérique Bidard, Laurent Duval, Fragkiskos D. Malliaros
2021 J jnl
Multiple Kernel Representation Learning on Networks.
CoRR
Abdulkadir Çelikkanat, Yanning Shen, Fragkiskos D. Malliaros
2021 J jnl
Topic-aware latent models for representation learning on networks.
CoRR
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
2021 J jnl
Topic-aware latent models for representation learning on networks.
Pattern Recognit. Lett.
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
2020 — conf
Boosting Tricks for Word Mover's Distance.
ICANN (2)
Konstantinos Skianis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, Michalis Vazirgiannis
2020 J jnl
Dynamic monitoring of software use with recurrent neural networks.
Data Knowl. Eng.
Chloé Adam, Antoine Aliotti, Fragkiskos D. Malliaros, Paul-Henry Cournède
2020 A* conf
Exponential Family Graph Embeddings.
AAAI
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
2020 A conf
Influence Maximization Using Influence and Susceptibility Embeddings.
ICWSM
George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2020 J jnl
NodeSig: Random Walk Diffusion meets Hashing for Scalable Graph Embeddings.
CoRR
Abdulkadir Çelikkanat, Apostolos N. Papadopoulos, Fragkiskos D. Malliaros
2020 J jnl
The core decomposition of networks: theory, algorithms and applications.
VLDB J.
Fragkiskos D. Malliaros, Christos Giatsidis, Apostolos N. Papadopoulos, Michalis Vazirgiannis
2019 J jnl
Exponential Family Graph Embeddings.
CoRR
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
2019 J jnl
Influence Maximization via Representation Learning.
CoRR
George Panagopoulos, Michalis Vazirgiannis, Fragkiskos D. Malliaros
2019 — conf
Kernel Node Embeddings.
GlobalSIP
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
2019 J jnl
Kernel Node Embeddings.
CoRR
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
2019 B conf
Perturb and combine to identify influential spreaders in real-world networks.
ASONAM
Antoine J.-P. Tixier, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Jesse Read, Michalis Vazirgiannis
2019 B conf
Semi-supervised learning and graph neural networks for fake news detection.
ASONAM
Adrien Benamira, Benjamin Devillers, Etienne Lesot, Ayush K. Ray, Manal Saadi, Fragkiskos D. Malliaros
2019 J jnl
k-Degree anonymity on directed networks.
Knowl. Inf. Syst.
Jordi Casas-Roma, Julián Salas, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2018 — conf
BiasedWalk: Biased Sampling for Representation Learning on Graphs.
IEEE BigData
Duong Nguyen, Fragkiskos D. Malliaros
2018 J jnl
BiasedWalk: Biased Sampling for Representation Learning on Graphs.
CoRR
Duong Nguyen, Fragkiskos D. Malliaros
2018 — conf
BigNet 2018 Chairs' Welcome & Organization.
WWW (Companion Volume)
Jie Tang, Michalis Vazirgiannis, Yuxiao Dong, Fragkiskos D. Malliaros, Michael Cochez, Mayank Kejriwal, Achim Rettinger
2018 — conf
DiffuGreedy: An Influence Maximization Algorithm Based on Diffusion Cascades.
COMPLEX NETWORKS (1)
George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2018 — conf
Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text Classification.
TextGraphs@NAACL-HLT
Konstantinos Skianis, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2018 A conf
GraphRep: Boosting Text Mining, NLP and Information Retrieval with Graphs.
CIKM
Michalis Vazirgiannis, Fragkiskos D. Malliaros, Giannis Nikolentzos
2018 J jnl
Perturb and Combine to Identify Influential Spreaders in Real-World Networks.
CoRR
Antoine J.-P. Tixier, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Jesse Read, Michalis Vazirgiannis
2018 J jnl
TNE: A Latent Model for Representation Learning on Networks.
CoRR
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
2017 A conf
Sensitivity of Community Structure to Network Uncertainty.
SDM
Marc Mitri, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2016 A* conf
A Graph Degeneracy-based Approach to Keyword Extraction.
EMNLP
Antoine J.-P. Tixier, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2016 J jnl
A k-core Decomposition Framework for Graph Clustering.
CoRR
Christos Giatsidis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, Charanpal Dhanjal, Emmanouil Kiagias, Dimitrios M. Thilikos, Michalis Vazirgiannis
2016 B conf
Core Decomposition in Graphs: Concepts, Algorithms and Applications.
EDBT
Fragkiskos D. Malliaros, Apostolos N. Papadopoulos, Michalis Vazirgiannis
2016 — conf
SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks.
ICDM Workshops
Konstantinos Skianis, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2015 J jnl
Estimating robustness in large social graphs.
Knowl. Inf. Syst.
Fragkiskos D. Malliaros, Vasileios Megalooikonomou, Christos Faloutsos
2015 B conf
Graph-Based Term Weighting for Text Categorization.
ASONAM
Fragkiskos D. Malliaros, Konstantinos Skianis
2015 — —
Mining Social and Information Networks: Dynamics and Applications. (Fouille de Données dans les Réseaux Sociaux et d'Information : Dynamiques et Applications ).
Fragkiskos D. Malliaros
2015 — conf
Spread it Good, Spread it Fast: Identification of Influential Nodes in Social Networks.
WWW (Companion Volume)
Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2014 A* conf
CoreCluster: A Degeneracy Based Graph Clustering Framework.
AAAI
Christos Giatsidis, Fragkiskos D. Malliaros, Dimitrios M. Thilikos, Michalis Vazirgiannis
2013 A conf
Advanced graph mining for community evaluation in social networks and the web.
WSDM
Christos Giatsidis, Fragkiskos D. Malliaros, Michalis Vazirgiannis
2013 J jnl
Clustering and Community Detection in Directed Networks: A Survey.
CoRR
Fragkiskos D. Malliaros, Michalis Vazirgiannis
2013 — conf
Multiresolution similarity search in time series data: an application to EEG signals.
PETRA
Amalia Charisi, Fragkiskos D. Malliaros, Evangelia I. Zacharaki, Vasileios Megalooikonomou
2013 A conf
To stay or not to stay: modeling engagement dynamics in social graphs.
CIKM
Fragkiskos D. Malliaros, Michalis Vazirgiannis
2012 A conf
Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection.
SDM
Fragkiskos D. Malliaros, Vasileios Megalooikonomou, Christos Faloutsos
2011 — conf
Expansion Properties of Large Social Graphs.
DASFAA Workshops
Fragkiskos D. Malliaros, Vasileios Megalooikonomou