Expansion Properties of Large Social Graphs. - Fragkiskos D. Malliaros; Vasileios Megalooikonomou (DASFAA Workshops, 2011)

Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection. - Fragkiskos D. Malliaros; Vasileios Megalooikonomou; Christos Faloutsos (SDM, 2012)

To stay or not to stay: modeling engagement dynamics in social graphs. - Fragkiskos D. Malliaros; Michalis Vazirgiannis (CIKM, 2013)

Multiresolution similarity search in time series data: an application to EEG signals. - Amalia Charisi; Fragkiskos D. Malliaros; Evangelia I. Zacharaki; Vasileios Megalooikonomou (PETRA, 2013)

Advanced graph mining for community evaluation in social networks and the web. - Christos Giatsidis; Fragkiskos D. Malliaros; Michalis Vazirgiannis (WSDM, 2013)

Clustering and Community Detection in Directed Networks: A Survey. - Fragkiskos D. Malliaros; Michalis Vazirgiannis (CoRR, 2013)

CoreCluster: A Degeneracy Based Graph Clustering Framework. - Christos Giatsidis; Fragkiskos D. Malliaros; Dimitrios M. Thilikos; Michalis Vazirgiannis (AAAI, 2014)

Graph-Based Term Weighting for Text Categorization. - Fragkiskos D. Malliaros; Konstantinos Skianis (ASONAM, 2015)

Spread it Good, Spread it Fast: Identification of Influential Nodes in Social Networks. - Maria-Evgenia G. Rossi; Fragkiskos D. Malliaros; Michalis Vazirgiannis (WWW (Companion Volume), 2015)

Estimating robustness in large social graphs. - Fragkiskos D. Malliaros; Vasileios Megalooikonomou; Christos Faloutsos (Knowl. Inf. Syst., 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)

Core Decomposition in Graphs: Concepts, Algorithms and Applications. - Fragkiskos D. Malliaros; Apostolos N. Papadopoulos; Michalis Vazirgiannis (EDBT, 2016)

A Graph Degeneracy-based Approach to Keyword Extraction. - Antoine J.-P. Tixier; Fragkiskos D. Malliaros; Michalis Vazirgiannis (EMNLP, 2016)

SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks. - Konstantinos Skianis; Maria-Evgenia G. Rossi; Fragkiskos D. Malliaros; Michalis Vazirgiannis (ICDM Workshops, 2016)

A k-core Decomposition Framework for Graph Clustering. - Christos Giatsidis; Fragkiskos D. Malliaros; Nikolaos Tziortziotis; Charanpal Dhanjal; Emmanouil Kiagias; Dimitrios M. Thilikos; Michalis Vazirgiannis (CoRR, 2016)

Sensitivity of Community Structure to Network Uncertainty. - Marc Mitri; Fragkiskos D. Malliaros; Michalis Vazirgiannis (SDM, 2017)

BiasedWalk: Biased Sampling for Representation Learning on Graphs. - Duong Nguyen; Fragkiskos D. Malliaros (IEEE BigData, 2018)

GraphRep: Boosting Text Mining, NLP and Information Retrieval with Graphs. - Michalis Vazirgiannis; Fragkiskos D. Malliaros; Giannis Nikolentzos (CIKM, 2018)

DiffuGreedy: An Influence Maximization Algorithm Based on Diffusion Cascades. - George Panagopoulos; Fragkiskos D. Malliaros; Michalis Vazirgiannis (COMPLEX NETWORKS (1), 2018)

Fusing Document, Collection and Label Graph-based Representations with Word Embeddings for Text Classification. - Konstantinos Skianis; Fragkiskos D. Malliaros; Michalis Vazirgiannis (TextGraphs@NAACL-HLT, 2018)

BigNet 2018 Chairs' Welcome & Organization. - Jie Tang 001; Michalis Vazirgiannis; Yuxiao Dong; Fragkiskos D. Malliaros; Michael Cochez; Mayank Kejriwal; Achim Rettinger (WWW (Companion Volume), 2018)

TNE: A Latent Model for Representation Learning on Networks. - Abdulkadir Çelikkanat; Fragkiskos D. Malliaros (CoRR, 2018)

Semi-supervised learning and graph neural networks for fake news detection. - Adrien Benamira; Benjamin Devillers; Etienne Lesot; Ayush K. Ray; Manal Saadi; Fragkiskos D. Malliaros (ASONAM, 2019)

Perturb and combine to identify influential spreaders in real-world networks. - Antoine J.-P. Tixier; Maria-Evgenia G. Rossi; Fragkiskos D. Malliaros; Jesse Read; Michalis Vazirgiannis (ASONAM, 2019)

Kernel Node Embeddings. - Abdulkadir Çelikkanat; Fragkiskos D. Malliaros (GlobalSIP, 2019)

Influence Maximization via Representation Learning. - George Panagopoulos; Michalis Vazirgiannis; Fragkiskos D. Malliaros (CoRR, 2019)

k-Degree anonymity on directed networks. - Jordi Casas-Roma; Julián Salas; Fragkiskos D. Malliaros; Michalis Vazirgiannis (Knowl. Inf. Syst., 2019)

Exponential Family Graph Embeddings. - Abdulkadir Çelikkanat; Fragkiskos D. Malliaros (AAAI, 2020)

Boosting Tricks for Word Mover's Distance. - Konstantinos Skianis; Fragkiskos D. Malliaros; Nikolaos Tziortziotis; Michalis Vazirgiannis (ICANN (2), 2020)

Influence Maximization Using Influence and Susceptibility Embeddings. - George Panagopoulos; Fragkiskos D. Malliaros; Michalis Vazirgiannis (ICWSM, 2020)

NodeSig: Random Walk Diffusion meets Hashing for Scalable Graph Embeddings. - Abdulkadir Çelikkanat; Apostolos N. Papadopoulos; Fragkiskos D. Malliaros (CoRR, 2020)

Dynamic monitoring of software use with recurrent neural networks. - Chloé Adam; Antoine Aliotti; Fragkiskos D. Malliaros; Paul-Henry Cournède (Data Knowl. Eng., 2020)

The core decomposition of networks: theory, algorithms and applications. - Fragkiskos D. Malliaros; Christos Giatsidis; Apostolos N. Papadopoulos; Michalis Vazirgiannis (VLDB J., 2020)

Multiomics Data Integration for Gene Regulatory Network Inference with Exponential Family Embeddings. - Surabhi Jaatan; Abdulkadir Çelikkanat; Aurelic Piravre; Frédérique Bidard; Laurent Duval; Fragkiskos D. Malliaros (EUSIPCO, 2021)

Influence Learning and Maximization. - George Panagopoulos; Fragkiskos D. Malliaros (ICWE, 2021)

An Adversarial Attacker for Neural Networks in Regression Problems. - Kavya Gupta; Jean-Christophe Pesquet; Béatrice Pesquet-Popescu; Fateh Kaakai; Fragkiskos D. Malliaros (AISafety@IJCAI, 2021)

GraphSVX: Shapley Value Explanations for Graph Neural Networks. - Alexandre Duval; Fragkiskos D. Malliaros (ECML/PKDD (2), 2021)

Learning to Maximize Influence. - George Panagopoulos; Nikolaos Tziortziotis; Fragkiskos D. Malliaros; Michalis Vazirgiannis (CoRR, 2021)

Topic-aware latent models for representation learning on networks. - Abdulkadir Çelikkanat; Fragkiskos D. Malliaros (Pattern Recognit. Lett., 2021)

NodeSig: Binary Node Embeddings via Random Walk Diffusion. - Abdulkadir Çelikkanat; Fragkiskos D. Malliaros; Apostolos N. Papadopoulos (ASONAM, 2022)

Higher-order Clustering and Pooling for Graph Neural Networks. - Alexandre Duval; Fragkiskos D. Malliaros (CIKM, 2022)

Multiple similarity drug-target interaction prediction with random walks and matrix factorization. - Bin Liu 058; Dimitrios Papadopoulos 004; Fragkiskos D. Malliaros; Grigorios Tsoumakas; Apostolos N. Papadopoulos (Briefings Bioinform., 2022)

BRANEnet: embedding multilayer networks for omics data integration. - Surabhi Jagtap; Aurélie Pirayre; Frédérique Bidard; Laurent Duval; Fragkiskos D. Malliaros (BMC Bioinform., 2022)

Understanding the Relationship between Over-smoothing and Over-squashing in Graph Neural Networks. - Jhony H. Giraldo; Fragkiskos D. Malliaros; Thierry Bouwmans (CoRR, 2022)

Multi-Task Learning for Influence Estimation and Maximization. - George Panagopoulos; Fragkiskos D. Malliaros; Michalis Vazirgiannis (IEEE Trans. Knowl. Data Eng., 2022)

BraneMF: integration of biological networks for functional analysis of proteins. - Surabhi Jagtap; Abdulkadir Çelikkanat; Aurélie Pirayre; Frédérique Bidard; Laurent Duval; Fragkiskos D. Malliaros (Bioinform., 2022)

Maximizing Influence with Graph Neural Networks. - George Panagopoulos; Nikolaos Tziortziotis; Michalis Vazirgiannis; Fragkiskos D. Malliaros (ASONAM, 2023)

On the Trade-off between Over-smoothing and Over-squashing in Deep Graph Neural Networks. - Jhony H. Giraldo; Konstantinos Skianis; Thierry Bouwmans; Fragkiskos D. Malliaros (CIKM, 2023)

Time-Varying Signals Recovery Via Graph Neural Networks. - Jhon A. Castro-Correa; Jhony H. Giraldo; Anindya Mondal; Mohsen Badiey; Thierry Bouwmans; Fragkiskos D. Malliaros (ICASSP, 2023)

Higher-Order Sparse Convolutions in Graph Neural Networks. - Jhony H. Giraldo; Sajid Javed; Arif Mahmood; Fragkiskos D. Malliaros; Thierry Bouwmans (ICASSP, 2023)

FAENet: Frame Averaging Equivariant GNN for Materials Modeling. - Alexandre Duval; Victor Schmidt; Alex Hernández-García; Santiago Miret; Fragkiskos D. Malliaros; Yoshua Bengio; David Rolnick (ICML, 2023)

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. - Alexandre Duval; Simon V. Mathis; Chaitanya K. Joshi; Victor Schmidt; Santiago Miret; Fragkiskos D. Malliaros; Taco Cohen; Pietro Lio; Yoshua Bengio; Michael M. Bronstein (CoRR, 2023)

Multiple Kernel Representation Learning on Networks. - Abdulkadir Çelikkanat; Yanning Shen; Fragkiskos D. Malliaros (IEEE Trans. Knowl. Data Eng., 2023)

A Machine Learning Tour in Network Science. - Fragkiskos D. Malliaros (2024)

The Factuality of Large Language Models in the Legal Domain. - Rajaa El Hamdani; Thomas Bonald; Fragkiskos D. Malliaros; Nils Holzenberger; Fabian M. Suchanek (CIKM, 2024)

Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation? - Daniele Malitesta; Emanuele Rossi; Claudio Pomo; Tommaso Di Noia; Fragkiskos D. Malliaros (CIKM, 2024)

Continuous Product Graph Neural Networks. - Aref Einizade; Fragkiskos D. Malliaros; Jhony H. Giraldo (NeurIPS, 2024)

Uplift Modeling Under Limited Supervision. - George Panagopoulos; Daniele Malitesta; Fragkiskos D. Malliaros; Jun Pang 001 (ECML/PKDD (6), 2024)

Graph Neural Networks for Treatment Effect Prediction. - George Panagopoulos; Daniele Malitesta; Fragkiskos D. Malliaros; Jun Pang 001 (CoRR, 2024)

Dealing with Missing Modalities in Multimodal Recommendation: a Feature Propagation-based Approach. - Daniele Malitesta; Emanuele Rossi; Claudio Pomo; Fragkiskos D. Malliaros; Tommaso Di Noia (CoRR, 2024)

Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks. - Aref Einizade; Fragkiskos D. Malliaros; Jhony H. Giraldo (CoRR, 2024)

Improving Molecular Modeling with Geometric GNNs: an Empirical Study. - Ali Ramlaoui; Théo Saulus; Basile Terver; Victor Schmidt; David Rolnick; Fragkiskos D. Malliaros; Alexandre Duval (CoRR, 2024)

How Fair is Your Diffusion Recommender Model? - Daniele Malitesta; Giacomo Medda; Erasmo Purificato; Ludovico Boratto; Fragkiskos D. Malliaros; Mirko Marras; Ernesto William De Luca (CoRR, 2024)

Centrality Graph Shift Operators for Graph Neural Networks. - Yassine Abbahaddou; Fragkiskos D. Malliaros; Johannes F. Lutzeyer; Michalis Vazirgiannis (CoRR, 2024)

Post-Hoc Robustness Enhancement in Graph Neural Networks with Conditional Random Fields. - Yassine Abbahaddou; Sofiane Ennadir; Johannes F. Lutzeyer; Fragkiskos D. Malliaros; Michalis Vazirgiannis (CoRR, 2024)

Gaussian Mixture Models Based Augmentation Enhances GNN Generalization. - Yassine Abbahaddou; Fragkiskos D. Malliaros; Johannes F. Lutzeyer; Amine Mohamed Aboussalah; Michalis Vazirgiannis (CoRR, 2024)

Estimation of a causal directed acyclic graph process using non-gaussianity. - Aref Einizade; Jhony H. Giraldo; Fragkiskos D. Malliaros; Sepideh Hajipour Sardouie (Digit. Signal Process., 2024)

Gegenbauer Graph Neural Networks for Time-Varying Signal Reconstruction. - Jhon A. Castro-Correa; Jhony H. Giraldo; Mohsen Badiey; Fragkiskos D. Malliaros (IEEE Trans. Neural Networks Learn. Syst., 2024)

Learning graph representations for influence maximization. - George Panagopoulos; Nikolaos Tziortziotis; Michalis Vazirgiannis; Jun Pang 001; Fragkiskos D. Malliaros (Soc. Netw. Anal. Min., 2024)

Piecewise Constant Spectral Graph Neural Network. - Vahan Martirosyan; Jhony H. Giraldo; Fragkiskos D. Malliaros (Trans. Mach. Learn. Res., 2025)

A Fused Gromov-Wasserstein Approach to Subgraph Contrastive Learning. - Amadou S. Sangare; Nicolas Dunou; Jhony H. Giraldo; Fragkiskos D. Malliaros (Trans. Mach. Learn. Res., 2025)

Cometh: A continuous-time discrete-state graph diffusion model. - Antoine Siraudin; Fragkiskos D. Malliaros; Christopher Morris 001 (Trans. Mach. Learn. Res., 2025)

Higher-Order GNNs Meet Efficiency: Sparse Sobolev Graph Neural Networks. - Jhony H. Giraldo; Aref Einizade; Andjela Todorovic; Jhon A. Castro-Correa; Mohsen Badiey; Thierry Bouwmans; Fragkiskos D. Malliaros (IEEE Trans. Signal Inf. Process. over Networks, 2025)

COSMOS: Continuous Simplicial Neural Networks. - Aref Einizade; Dorina Thanou; Fragkiskos D. Malliaros; Jhony H. Giraldo (CoRR, 2025)

FAROS: Fair Graph Generation via Attribute Switching Mechanisms. - Abdennacer Badaoui; Oussama Kharouiche; Hatim Mrabet; Daniele Malitesta; Fragkiskos D. Malliaros (CoRR, 2025)