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Malliaros, Fragkiskos D.
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1

Gegenbauer Graph Neural Networks for Time-Varying Signal Re..:

Castro-Correa, Jhon A. ; Giraldo, Jhony H. ; Badiey, Mohsen.
IEEE Transactions on Neural Networks and Learning Systems.  , 2024
Link: https://doi.org/10.1109/..
 
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2

Estimation of a causal directed acyclic graph process using..:

Einizade, Aref ; Giraldo, Jhony H. ; Malliaros, Fragkiskos D..
Digital Signal Processing.  146 (2024)  - p. 104400 , 2024
Link: https://doi.org/10.1016/..
 
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3

Maximizing Influence with Graph Neural Networks:

, In: Proceedings of the 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining,
Panagopoulos, George ; Tziortziotis, Nikolaos ; Vazirgiannis, Michalis. - p. 237-244 , 2023
Link: https://dl.acm.org/doi/1..
 
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4

Higher-Order Sparse Convolutions in Graph Neural Networks:

, In: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
Giraldo, Jhony H. ; Javed, Sajid ; Mahmood, Arif.. - p. 1-5 , 2023
Link: https://doi.org/10.1109/..
 
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5

Time-Varying Signals Recovery Via Graph Neural Networks:

, In: ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP),
Castro-Correa, Jhon A. ; Giraldo, Jhony H. ; Mondal, Anindya... - p. 1-5 , 2023
Link: https://doi.org/10.1109/..
 
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6

On the Trade-off between Over-smoothing and Over-squashing ..:

, In: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management,
Giraldo, Jhony H. ; Skianis, Konstantinos ; Bouwmans, Thierry. - p. 566-576 , 2023
Link: https://dl.acm.org/doi/1..
 
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7

NodeSig: Binary Node Embeddings via Random Walk Diffusion:

, In: 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM),
Celikkanat, Abdulkadir ; Malliaros, Fragkiskos D. ; Papadopoulos, Apostolos N. - p. 68-75 , 2022
Link: https://doi.org/10.1109/..
 
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8

Multiple Kernel Representation Learning on Networks:

Celikkanat, Abdulkadir ; Shen, Yanning ; Malliaros, Fragkiskos
IEEE Transactions on Knowledge and Data Engineering.  , 2022
Link: https://doi.org/10.1109/..
 
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9

BRANEnet: embedding multilayer networks for omics data inte..:

Jagtap, Surabhi ; Pirayre, Aurélie ; Bidard, Frédérique..
BMC Bioinformatics.  23 (2022)  1 - p. , 2022
Link: https://doi.org/10.1186/..
 
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10

Multivariate Lipschitz Analysis of the Stability of Neural ..:

Gupta, Kavya ; Kaakai, Fateh ; Pesquet-Popescu, Beatrice..
Frontiers in Signal Processing.  2 (2022)  - p. , 2022
Link: https://doi.org/10.3389/..
 
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11

Multi-Task Learning for Influence Estimation and Maximizati..:

Panagopoulos, George ; Malliaros, Fragkiskos D. ; Vazirgiannis, Michalis
IEEE Transactions on Knowledge and Data Engineering.  34 (2022)  9 - p. 4398-4409 , 2022
Link: https://doi.org/10.1109/..
 
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12

Multiple similarity drug–target interaction prediction with..:

Liu, Bin ; Papadopoulos, Dimitrios ; Malliaros, Fragkiskos D..
Briefings in Bioinformatics.  23 (2022)  5 - p. , 2022
Link: https://doi.org/10.1093/..
 
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13

Higher-order Clustering and Pooling for Graph Neural Networ..:

, In: Proceedings of the 31st ACM International Conference on Information & Knowledge Management,
Duval, Alexandre ; Malliaros, Fragkiskos - p. 426-435 , 2022
Link: https://dl.acm.org/doi/1..
 
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14

Influence Learning and Maximization:

, In: Lecture Notes in Computer Science; Web Engineering,
Panagopoulos, George ; Malliaros, Fragkiskos D. - p. 547-550 , 2021
Link: https://doi.org/10.1007/..
 
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15

GraphSVX: Shapley Value Explanations for Graph Neural Netwo..:

, In: Machine Learning and Knowledge Discovery in Databases. Research Track; Lecture Notes in Computer Science,
Duval, Alexandre ; Malliaros, Fragkiskos D. - p. 302-318 , 2021
Link: https://doi.org/10.1007/..
 
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