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Fragkiskos D. Malliaros
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2020 – today
- 2024
- [b2]Fragkiskos D. Malliaros:
A Machine Learning Tour in Network Science. University of Paris-Saclay, France, 2024 - [j13]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: 104400 (2024) - [j12]George Panagopoulos, Nikolaos Tziortziotis, Michalis Vazirgiannis, Jun Pang, Fragkiskos D. Malliaros:
Learning graph representations for influence maximization. Soc. Netw. Anal. Min. 14(1): 203 (2024) - [j11]Jhon A. Castro-Correa, Jhony H. Giraldo, Mohsen Badiey, Fragkiskos D. Malliaros:
Gegenbauer Graph Neural Networks for Time-Varying Signal Reconstruction. IEEE Trans. Neural Networks Learn. Syst. 35(9): 11734-11745 (2024) - [c35]George Panagopoulos, Daniele Malitesta, Fragkiskos D. Malliaros, Jun Pang:
Uplift Modeling Under Limited Supervision. ECML/PKDD (6) 2024: 127-144 - [i29]George Panagopoulos, Daniele Malitesta, Fragkiskos D. Malliaros, Jun Pang:
Graph Neural Networks for Treatment Effect Prediction. CoRR abs/2403.19289 (2024) - [i28]Jhon A. Castro-Correa, Jhony H. Giraldo, Mohsen Badiey, Fragkiskos D. Malliaros:
Gegenbauer Graph Neural Networks for Time-varying Signal Reconstruction. CoRR abs/2403.19800 (2024) - [i27]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) - [i26]Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo:
Continuous Product Graph Neural Networks. CoRR abs/2405.18877 (2024) - [i25]Aref Einizade, Fragkiskos D. Malliaros, Jhony H. Giraldo:
Spatiotemporal Forecasting Meets Efficiency: Causal Graph Process Neural Networks. CoRR abs/2405.18879 (2024) - [i24]Antoine Siraudin, Fragkiskos D. Malliaros, Christopher Morris:
Cometh: A continuous-time discrete-state graph diffusion model. CoRR abs/2406.06449 (2024) - [i23]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 abs/2407.08313 (2024) - [i22]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) - [i21]Daniele Malitesta, Giacomo Medda, Erasmo Purificato, Ludovico Boratto, Fragkiskos D. Malliaros, Mirko Marras, Ernesto William De Luca:
How Fair is Your Diffusion Recommender Model? CoRR abs/2409.04339 (2024) - 2023
- [j10]Abdulkadir Çelikkanat, Yanning Shen, Fragkiskos D. Malliaros:
Multiple Kernel Representation Learning on Networks. IEEE Trans. Knowl. Data Eng. 35(6): 6113-6125 (2023) - [c34]George Panagopoulos, Nikolaos Tziortziotis, Michalis Vazirgiannis, Fragkiskos D. Malliaros:
Maximizing Influence with Graph Neural Networks. ASONAM 2023: 237-244 - [c33]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: 566-576 - [c32]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: 1-5 - [c31]Jhony H. Giraldo, Sajid Javed, Arif Mahmood, Fragkiskos D. Malliaros, Thierry Bouwmans:
Higher-Order Sparse Convolutions in Graph Neural Networks. ICASSP 2023: 1-5 - [c30]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: 9013-9033 - [i20]Jhony H. Giraldo, Sajid Javed, Arif Mahmood, Fragkiskos D. Malliaros, Thierry Bouwmans:
Higher-order Sparse Convolutions in Graph Neural Networks. CoRR abs/2302.10505 (2023) - [i19]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 abs/2302.11313 (2023) - [i18]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 abs/2305.05577 (2023) - [i17]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 abs/2312.07511 (2023) - 2022
- [j9]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) - [j8]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): 5383-5389 (2022) - [j7]Surabhi Jagtap, Aurélie Pirayre, Frédérique Bidard, Laurent Duval, Fragkiskos D. Malliaros:
BRANEnet: embedding multilayer networks for omics data integration. BMC Bioinform. 23(1): 429 (2022) - [j6]George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
Multi-Task Learning for Influence Estimation and Maximization. IEEE Trans. Knowl. Data Eng. 34(9): 4398-4409 (2022) - [c29]Abdulkadir Çelikkanat, Fragkiskos D. Malliaros, Apostolos N. Papadopoulos:
NodeSig: Binary Node Embeddings via Random Walk Diffusion. ASONAM 2022: 68-75 - [c28]Alexandre Duval, Fragkiskos D. Malliaros:
Higher-order Clustering and Pooling for Graph Neural Networks. CIKM 2022: 426-435 - [i16]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 abs/2201.09508 (2022) - [i15]Alexandre Duval, Fragkiskos D. Malliaros:
Higher-order Clustering and Pooling for Graph Neural Networks. CoRR abs/2209.03473 (2022) - [i14]Jhony H. Giraldo, Fragkiskos D. Malliaros, Thierry Bouwmans:
Understanding the Relationship between Over-smoothing and Over-squashing in Graph Neural Networks. CoRR abs/2212.02374 (2022) - 2021
- [j5]Abdulkadir Çelikkanat, Fragkiskos D. Malliaros:
Topic-aware latent models for representation learning on networks. Pattern Recognit. Lett. 144: 89-96 (2021) - [c27]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: 1221-1225 - [c26]George Panagopoulos, Fragkiskos D. Malliaros:
Influence Learning and Maximization. ICWE 2021: 547-550 - [c25]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 - [c24]Alexandre Duval, Fragkiskos D. Malliaros:
GraphSVX: Shapley Value Explanations for Graph Neural Networks. ECML/PKDD (2) 2021: 302-318 - [i13]Alexandre Duval, Fragkiskos D. Malliaros:
GraphSVX: Shapley Value Explanations for Graph Neural Networks. CoRR abs/2104.10482 (2021) - [i12]Abdulkadir Çelikkanat, Yanning Shen, Fragkiskos D. Malliaros:
Multiple Kernel Representation Learning on Networks. CoRR abs/2106.05057 (2021) - [i11]George Panagopoulos, Nikolaos Tziortziotis, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
Learning to Maximize Influence. CoRR abs/2108.04623 (2021) - [i10]Abdulkadir Çelikkanat, Fragkiskos D. Malliaros:
Topic-aware latent models for representation learning on networks. CoRR abs/2111.05576 (2021) - 2020
- [j4]Chloé Adam, Antoine Aliotti, Fragkiskos D. Malliaros, Paul-Henry Cournède:
Dynamic monitoring of software use with recurrent neural networks. Data Knowl. Eng. 125: 101781 (2020) - [j3]Fragkiskos D. Malliaros, Christos Giatsidis, Apostolos N. Papadopoulos, Michalis Vazirgiannis:
The core decomposition of networks: theory, algorithms and applications. VLDB J. 29(1): 61-92 (2020) - [c23]Abdulkadir Çelikkanat, Fragkiskos D. Malliaros:
Exponential Family Graph Embeddings. AAAI 2020: 3357-3364 - [c22]Konstantinos Skianis, Fragkiskos D. Malliaros, Nikolaos Tziortziotis, Michalis Vazirgiannis:
Boosting Tricks for Word Mover's Distance. ICANN (2) 2020: 761-772 - [c21]George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
Influence Maximization Using Influence and Susceptibility Embeddings. ICWSM 2020: 511-521 - [i9]Abdulkadir Çelikkanat, Apostolos N. Papadopoulos, Fragkiskos D. Malliaros:
NodeSig: Random Walk Diffusion meets Hashing for Scalable Graph Embeddings. CoRR abs/2010.00261 (2020)
2010 – 2019
- 2019
- [j2]Jordi Casas-Roma, Julián Salas, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
k-Degree anonymity on directed networks. Knowl. Inf. Syst. 61(3): 1743-1768 (2019) - [c20]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: 73-80 - [c19]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: 568-569 - [c18]Abdulkadir Çelikkanat, Fragkiskos D. Malliaros:
Kernel Node Embeddings. GlobalSIP 2019: 1-5 - [i8]George Panagopoulos, Michalis Vazirgiannis, Fragkiskos D. Malliaros:
Influence Maximization via Representation Learning. CoRR abs/1904.08804 (2019) - [i7]Abdulkadir Çelikkanat, Fragkiskos D. Malliaros:
Kernel Node Embeddings. CoRR abs/1909.03416 (2019) - [i6]Abdulkadir Çelikkanat, Fragkiskos D. Malliaros:
Exponential Family Graph Embeddings. CoRR abs/1911.09007 (2019) - 2018
- [c17]Duong Nguyen, Fragkiskos D. Malliaros:
BiasedWalk: Biased Sampling for Representation Learning on Graphs. IEEE BigData 2018: 4045-4053 - [c16]Michalis Vazirgiannis, Fragkiskos D. Malliaros, Giannis Nikolentzos:
GraphRep: Boosting Text Mining, NLP and Information Retrieval with Graphs. CIKM 2018: 2295-2296 - [c15]George Panagopoulos, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
DiffuGreedy: An Influence Maximization Algorithm Based on Diffusion Cascades. COMPLEX NETWORKS (1) 2018: 392-404 - [c14]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: 49-58 - [c13]Jie Tang, Michalis Vazirgiannis, Yuxiao Dong, Fragkiskos D. Malliaros, Michael Cochez, Mayank Kejriwal, Achim Rettinger:
BigNet 2018 Chairs' Welcome & Organization. WWW (Companion Volume) 2018: 943-944 - [i5]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 abs/1807.09586 (2018) - [i4]Duong Nguyen, Fragkiskos D. Malliaros:
BiasedWalk: Biased Sampling for Representation Learning on Graphs. CoRR abs/1809.02482 (2018) - [i3]Abdulkadir Çelikkanat, Fragkiskos D. Malliaros:
TNE: A Latent Model for Representation Learning on Networks. CoRR abs/1810.06917 (2018) - 2017
- [c12]Marc Mitri, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
Sensitivity of Community Structure to Network Uncertainty. SDM 2017: 345-353 - 2016
- [c11]Fragkiskos D. Malliaros, Apostolos N. Papadopoulos, Michalis Vazirgiannis:
Core Decomposition in Graphs: Concepts, Algorithms and Applications. EDBT 2016: 720-721 - [c10]Antoine J.-P. Tixier, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
A Graph Degeneracy-based Approach to Keyword Extraction. EMNLP 2016: 1860-1870 - [c9]Konstantinos Skianis, Maria-Evgenia G. Rossi, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
SpreadViz: Analytics and Visualization of Spreading Processes in Social Networks. ICDM Workshops 2016: 1324-1327 - [i2]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 abs/1607.02096 (2016) - 2015
- [b1]Fragkiskos D. Malliaros:
Mining Social and Information Networks: Dynamics and Applications. (Fouille de Données dans les Réseaux Sociaux et d'Information : Dynamiques et Applications ). École Polytechnique, Palaiseau, France, 2015 - [j1]Fragkiskos D. Malliaros, Vasileios Megalooikonomou, Christos Faloutsos:
Estimating robustness in large social graphs. Knowl. Inf. Syst. 45(3): 645-678 (2015) - [c8]Fragkiskos D. Malliaros, Konstantinos Skianis:
Graph-Based Term Weighting for Text Categorization. ASONAM 2015: 1473-1479 - [c7]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: 101-102 - 2014
- [c6]Christos Giatsidis, Fragkiskos D. Malliaros, Dimitrios M. Thilikos, Michalis Vazirgiannis:
CoreCluster: A Degeneracy Based Graph Clustering Framework. AAAI 2014: 44-50 - 2013
- [c5]Fragkiskos D. Malliaros, Michalis Vazirgiannis:
To stay or not to stay: modeling engagement dynamics in social graphs. CIKM 2013: 469-478 - [c4]Amalia Charisi, Fragkiskos D. Malliaros, Evangelia I. Zacharaki, Vasileios Megalooikonomou:
Multiresolution similarity search in time series data: an application to EEG signals. PETRA 2013: 33:1-33:8 - [c3]Christos Giatsidis, Fragkiskos D. Malliaros, Michalis Vazirgiannis:
Advanced graph mining for community evaluation in social networks and the web. WSDM 2013: 771-772 - [i1]Fragkiskos D. Malliaros, Michalis Vazirgiannis:
Clustering and Community Detection in Directed Networks: A Survey. CoRR abs/1308.0971 (2013) - 2012
- [c2]Fragkiskos D. Malliaros, Vasileios Megalooikonomou, Christos Faloutsos:
Fast Robustness Estimation in Large Social Graphs: Communities and Anomaly Detection. SDM 2012: 942-953 - 2011
- [c1]Fragkiskos D. Malliaros, Vasileios Megalooikonomou:
Expansion Properties of Large Social Graphs. DASFAA Workshops 2011: 311-322
Coauthor Index
aka: Jhony H. Giraldo
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last updated on 2024-10-15 20:47 CEST by the dblp team
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