Fragkiskos D. Malliaros

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 62

Top Venues

École Polytechnique, Palaiseau, France (PHD)

Education History

École Polytechnique, Palaiseau, France

PHD

Publications

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 (2024)
George Panagopoulos, Daniele Malitesta, Fragkiskos D. Malliaros, Jun Pang
Graph Neural Networks for Treatment Effect Prediction. CoRR (2024)
Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo
Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks. CoRR (2024)
Antoine Siraudin, Fragkiskos D. Malliaros, Christopher Morris
Cometh: A continuous-time discrete-state graph diffusion model. CoRR (2024)
Aref Einizade, Jhony H. Giraldo, Fragkiskos D. Malliaros, Sepideh Hajipour Sardouie
Estimation of a causal directed acyclic graph process using non-gaussianity. Digit. Signal Process. 146 (2024)
Ali Ramlaoui, Théo Saulus, Basile Terver, Victor Schmidt, David Rolnick, Fragkiskos D. Malliaros, Alexandre Duval
Improving Molecular Modeling with Geometric GNNs: an Empirical Study. CoRR (2024)
Jhon A. Castro-Correa, Jhony H. Giraldo, Mohsen Badiey, Fragkiskos D. Malliaros
Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction. CoRR (2024)
Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo
Continuous Product Graph Neural Networks. CoRR (2024)
Jhony H. Giraldo, Sajid Javed, Arif Mahmood, Fragkiskos D. Malliaros, Thierry Bouwmans
Higher-order Sparse Convolutions in Graph Neural Networks. CoRR (2023)
Jhony H. Giraldo, Sajid Javed, Arif Mahmood, Fragkiskos D. Malliaros, Thierry Bouwmans
Higher-Order Sparse Convolutions in Graph Neural Networks. ICASSP (2023)
Abdulkadir Çelikkanat, Yanning Shen, Fragkiskos D. Malliaros
Multiple Kernel Representation Learning on Networks. IEEE Trans. Knowl. Data Eng. 35 (6) (2023)
Alexandre Duval, Simon V. Mathis, Chaitanya K. Joshi, Victor Schmidt, Santiago Miret, Fragkiskos D. Malliaros, Taco Cohen, Pietro Lio, Yoshua Bengio, Michael M. Bronstein
A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. CoRR (2023)
Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
FAENet: Frame Averaging Equivariant GNN for Materials Modeling. CoRR (2023)
Jhon A. Castro-Correa, Jhony H. Giraldo, Anindya Mondal, Mohsen Badiey, Thierry Bouwmans, Fragkiskos D. Malliaros
Time-varying Signals Recovery via Graph Neural Networks. CoRR (2023)
Jhony H. Giraldo, Konstantinos Skianis, Thierry Bouwmans, Fragkiskos D. Malliaros
On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks. CIKM (2023)
Alexandre Duval, Victor Schmidt, Alex Hernández-García, Santiago Miret, Fragkiskos D. Malliaros, Yoshua Bengio, David Rolnick
FAENet: Frame Averaging Equivariant GNN for Materials Modeling. ICML (2023)
Jhon A. Castro-Correa, Jhony H. Giraldo, Anindya Mondal, Mohsen Badiey, Thierry Bouwmans, Fragkiskos D. Malliaros
Time-Varying Signals Recovery Via Graph Neural Networks. ICASSP (2023)
George Panagopoulos, Nikolaos Tziortziotis, Michalis Vazirgiannis, Fragkiskos D. Malliaros
Maximizing Influence with Graph Neural Networks. ASONAM (2023)
Jhony H. Giraldo, Fragkiskos D. Malliaros, Thierry Bouwmans
Understanding the Relationship between Over-smoothing and Over-squashing in Graph Neural Networks. CoRR (2022)
Alexandre Duval, Fragkiskos D. Malliaros
Higher-order Clustering and Pooling for Graph Neural Networks. CoRR (2022)
Surabhi Jagtap, Abdulkadir Çelikkanat, Aurélie Pirayre, Frédérique Bidard, Laurent Duval, Fragkiskos D. Malliaros
BraneMF: integration of biological networks for functional analysis of proteins. Bioinform. 38 (24) (2022)
Surabhi Jagtap, Aurélie Pirayre, Frédérique Bidard, Laurent Duval, Fragkiskos D. Malliaros
BRANEnet: embedding multilayer networks for omics data integration. BMC Bioinform. 23 (1) (2022)
Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros, Grigorios Tsoumakas, Apostolos N. Papadopoulos
Multiple similarity drug-target interaction prediction with random walks and matrix factorization. Briefings Bioinform. 23 (5) (2022)
George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis
Multi-Task Learning for Influence Estimation and Maximization. IEEE Trans. Knowl. Data Eng. 34 (9) (2022)
Bin Liu, Dimitrios Papadopoulos, Fragkiskos D. Malliaros, Grigorios Tsoumakas, Apostolos N. Papadopoulos
Multiple Similarity Drug-Target Interaction Prediction with Random Walks and Matrix Factorization. CoRR (2022)
Alexandre Duval, Fragkiskos D. Malliaros
Higher-order Clustering and Pooling for Graph Neural Networks. CIKM (2022)
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros, Apostolos N. Papadopoulos
NodeSig: Binary Node Embeddings via Random Walk Diffusion. ASONAM (2022)
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
Topic-aware latent models for representation learning on networks. CoRR (2021)
George Panagopoulos, Nikolaos Tziortziotis, Fragkiskos D. Malliaros, Michalis Vazirgiannis
Learning to Maximize Influence. CoRR (2021)
Abdulkadir Çelikkanat, Yanning Shen, Fragkiskos D. Malliaros
Multiple Kernel Representation Learning on Networks. CoRR (2021)
George Panagopoulos, Fragkiskos D. Malliaros
Influence Learning and Maximization. ICWE (2021)
Surabhi Jaatan, Abdulkadir Çelikkanat, Aurelic Piravre, Frédérique Bidard, Laurent Duval, Fragkiskos D. Malliaros
Multiomics Data Integration for Gene Regulatory Network Inference with Exponential Family Embeddings. EUSIPCO (2021)
Alexandre Duval, Fragkiskos D. Malliaros
GraphSVX: Shapley Value Explanations for Graph Neural Networks. ECML/PKDD (2) (2021)
Kavya Gupta, Jean-Christophe Pesquet, Béatrice Pesquet-Popescu, Fateh Kaakai, Fragkiskos D. Malliaros
An Adversarial Attacker for Neural Networks in Regression Problems. AISafety@IJCAI (2021)
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
Topic-aware latent models for representation learning on networks. Pattern Recognit. Lett. 144 (2021)
Alexandre Duval, Fragkiskos D. Malliaros
GraphSVX: Shapley Value Explanations for Graph Neural Networks. CoRR (2021)
George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis
Influence Maximization Using Influence and Susceptibility Embeddings. ICWSM (2020)
Fragkiskos D. Malliaros, Christos Giatsidis, Apostolos N. Papadopoulos, Michalis Vazirgiannis
The core decomposition of networks: theory, algorithms and applications. VLDB J. 29 (1) (2020)
Konstantinos Skianis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, Michalis Vazirgiannis
Boosting Tricks for Word Mover's Distance. ICANN (2) (2020)
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
Exponential Family Graph Embeddings. AAAI (2020)
Chloé Adam, Antoine Aliotti, Fragkiskos D. Malliaros, Paul-Henry Cournède
Dynamic monitoring of software use with recurrent neural networks. Data Knowl. Eng. 125 (2020)
Abdulkadir Çelikkanat, Apostolos N. Papadopoulos, Fragkiskos D. Malliaros
NodeSig: Random Walk Diffusion meets Hashing for Scalable Graph Embeddings. CoRR (2020)
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
Kernel Node Embeddings. GlobalSIP (2019)
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
Kernel Node Embeddings. CoRR (2019)
George Panagopoulos, Michalis Vazirgiannis, Fragkiskos D. Malliaros
Influence Maximization via Representation Learning. CoRR (2019)
Jordi Casas-Roma, Julián Salas, Fragkiskos D. Malliaros, Michalis Vazirgiannis
k-Degree anonymity on directed networks. Knowl. Inf. Syst. 61 (3) (2019)
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
Exponential Family Graph Embeddings. CoRR (2019)
Adrien Benamira, Benjamin Devillers, Etienne Lesot, Ayush K. Ray, Manal Saadi, Fragkiskos D. Malliaros
Semi-supervised learning and graph neural networks for fake news detection. ASONAM (2019)
Antoine J.-P. Tixier, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Jesse Read, Michalis Vazirgiannis
Perturb and combine to identify influential spreaders in real-world networks. ASONAM (2019)
Duong Nguyen, Fragkiskos D. Malliaros
BiasedWalk: Biased Sampling for Representation Learning on Graphs. CoRR (2018)
Duong Nguyen, Fragkiskos D. Malliaros
BiasedWalk: Biased Sampling for Representation Learning on Graphs. IEEE BigData (2018)
Abdulkadir Çelikkanat, Fragkiskos D. Malliaros
TNE: A Latent Model for Representation Learning on Networks. CoRR (2018)
Konstantinos Skianis, Fragkiskos D. Malliaros, Michalis Vazirgiannis
Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text Classification. TextGraphs@NAACL-HLT (2018)
Jie Tang, Michalis Vazirgiannis, Yuxiao Dong, Fragkiskos D. Malliaros, Michael Cochez, Mayank Kejriwal, Achim Rettinger
BigNet 2018 Chairs' Welcome & Organization. WWW (Companion Volume) (2018)
Antoine J.-P. Tixier, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Jesse Read, Michalis Vazirgiannis
Perturb and Combine to Identify Influential Spreaders in Real-World Networks. CoRR (2018)
Michalis Vazirgiannis, Fragkiskos D. Malliaros, Giannis Nikolentzos
GraphRep: Boosting Text Mining, NLP and Information Retrieval with Graphs. CIKM (2018)
George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis
DiffuGreedy: An Influence Maximization Algorithm Based on Diffusion Cascades. COMPLEX NETWORKS (1) (2018)
Marc Mitri, Fragkiskos D. Malliaros, Michalis Vazirgiannis
Sensitivity of Community Structure to Network Uncertainty. SDM (2017)
Christos Giatsidis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, Charanpal Dhanjal, Emmanouil Kiagias, Dimitrios M. Thilikos, Michalis Vazirgiannis
A k-core Decomposition Framework for Graph Clustering. CoRR (2016)
Konstantinos Skianis, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Michalis Vazirgiannis
SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks. ICDM Workshops (2016)
Antoine J.-P. Tixier, Fragkiskos D. Malliaros, Michalis Vazirgiannis
A Graph Degeneracy-based Approach to Keyword Extraction. EMNLP (2016)
Fragkiskos D. Malliaros, Apostolos N. Papadopoulos, Michalis Vazirgiannis
Core Decomposition in Graphs: Concepts, Algorithms and Applications. EDBT (2016)
Fragkiskos D. Malliaros, Vasileios Megalooikonomou, Christos Faloutsos
Estimating robustness in large social graphs. Knowl. Inf. Syst. 45 (3) (2015)
Fragkiskos D. Malliaros, Konstantinos Skianis
Graph-Based Term Weighting for Text Categorization. ASONAM (2015)
Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Michalis Vazirgiannis
Spread it Good, Spread it Fast: Identification of Influential Nodes in Social Networks. WWW (Companion Volume) (2015)
Christos Giatsidis, Fragkiskos D. Malliaros, Dimitrios M. Thilikos, Michalis Vazirgiannis
CoreCluster: A Degeneracy Based Graph Clustering Framework. AAAI (2014)
Fragkiskos D. Malliaros, Michalis Vazirgiannis
Clustering and Community Detection in Directed Networks: A Survey. CoRR (2013)
Fragkiskos D. Malliaros, Michalis Vazirgiannis
To stay or not to stay: modeling engagement dynamics in social graphs. CIKM (2013)
Amalia Charisi, Fragkiskos D. Malliaros, Evangelia I. Zacharaki, Vasileios Megalooikonomou
Multiresolution similarity search in time series data: an application to EEG signals. PETRA (2013)
Christos Giatsidis, Fragkiskos D. Malliaros, Michalis Vazirgiannis
Advanced graph mining for community evaluation in social networks and the web. WSDM (2013)
Fragkiskos D. Malliaros, Vasileios Megalooikonomou, Christos Faloutsos
Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection. SDM (2012)
Fragkiskos D. Malliaros, Vasileios Megalooikonomou
Expansion Properties of Large Social Graphs. DASFAA Workshops (2011)

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Publication Activity (10 Years)

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Fragkiskos D. Malliaros