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ORCIDCharilaos I. Kanatsoulis
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2020 – today
- 2024
[c17]Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Graph Neural Networks are More Powerful than We Think. ICASSP 2024: 7550-7554- [c16]Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Counting Graph Substructures with Graph Neural Networks. ICLR 2024 - [c15]Panagiotis A. Traganitis, Charilaos I. Kanatsoulis:
A Graph Autoencoder Approach to Crowdsourcing. SAM 2024: 1-5 - [i13]Shreyas Muthusamy, Damian Owerko, Charilaos I. Kanatsoulis, Saurav Agarwal, Alejandro Ribeiro:
Generalizability of Graph Neural Networks for Decentralized Unlabeled Motion Planning. CoRR abs/2409.19829 (2024) - 2023
- [c14]Damian Owerko, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Solving Large-Scale Spatial Problems with Convolutional Neural Networks. ACSSC 2023: 1064-1069 - [c13]Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk, Donald J. Bucci, Alejandro Ribeiro:
Multi-Target Tracking with Transferable Convolutional Neural Networks. CAMSAP 2023: 56-60 - [c12]Samar Hadou
, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Space-Time Graph Neural Networks with Stochastic Graph Perturbations. ICASSP 2023: 1-5 - [i12]Damian Owerko, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Solving Large-scale Spatial Problems with Convolutional Neural Networks. CoRR abs/2306.08191 (2023) - [i11]Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk, Donald J. Bucci Jr., Alejandro Ribeiro:
Transferability of Convolutional Neural Networks in Stationary Learning Tasks. CoRR abs/2307.11588 (2023) - [i10]Jiashu He, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Network Alignment with Transferable Graph Autoencoders. CoRR abs/2310.03272 (2023) - 2022
- [c11]Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Space-Time Graph Neural Networks. ICLR 2022 - [c10]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
GAGE: Geometry Preserving Attributed Graph Embeddings. WSDM 2022: 439-448 - [i9]Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Graph Neural Networks Are More Powerful Than we Think. CoRR abs/2205.09801 (2022) - [i8]Damian Owerko, Charilaos I. Kanatsoulis, Alejandro Ribeiro, Donald J. Bucci Jr., Jennifer Bondarchuk:
Deep Convolutional Neural Networks for Multi-Target Tracking: A Transfer Learning Approach. CoRR abs/2210.15539 (2022) - [i7]Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Space-Time Graph Neural Networks with Stochastic Graph Perturbations. CoRR abs/2210.16270 (2022) - 2021
- [j5]Faisal M. Almutairi, Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
Prema: Principled Tensor Data Recovery From Multiple Aggregated Views. IEEE J. Sel. Top. Signal Process. 15(3): 535-549 (2021) - [j4]Mikael Sørensen, Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
Generalized Canonical Correlation Analysis: A Subspace Intersection Approach. IEEE Trans. Signal Process. 69: 2452-2467 (2021) - [c9]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
TeX-Graph: Coupled tensor-matrix knowledge-graph embedding for COVID-19 drug repurposing. SDM 2021: 603-611 - [i6]Samar Hadou, Charilaos I. Kanatsoulis, Alejandro Ribeiro:
Space-Time Graph Neural Networks. CoRR abs/2110.02880 (2021) - 2020
- [j3]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mehmet Akçakaya:
Tensor Completion From Regular Sub-Nyquist Samples. IEEE Trans. Signal Process. 68: 1-16 (2020) - [c8]Mohamed Salah Ibrahim, Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
Downlink Channel Feedback for FDD Massive MIMO Systems via Tensor Compression and Sampling. ACSSC 2020: 27-31 - [c7]Faisal M. Almutairi, Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
Tendi: Tensor Disaggregation from Multiple Coarse Views. PAKDD (2) 2020: 867-880 - [i5]Mikael Sørensen, Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
Generalized Canonical Correlation Analysis: A Subspace Intersection Approach. CoRR abs/2003.11205 (2020) - [i4]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
TeX-Graph: Coupled tensor-matrix knowledge-graph embedding for COVID-19 drug repurposing. CoRR abs/2010.11367 (2020) - [i3]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
GAGE: Geometry Preserving Attributed Graph Embeddings. CoRR abs/2011.01422 (2020)
2010 – 2019
- 2019
- [j2]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data. IEEE Trans. Signal Process. 67(2): 306-319 (2019) - [c6]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
Large-scale Canonical Polyadic Decomposition via Regular Tensor Sampling. EUSIPCO 2019: 1-5 - [c5]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos, Mehmet Akçakaya, Xiao Fu:
Regular Sampling of Tensor Signals: Theory and Application to FMRI. ICASSP 2019: 2932-2936 - [i2]Faisal M. Almutairi, Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
PREMA: Principled Tensor Data Recovery from Multiple Aggregated Views. CoRR abs/1910.12001 (2019) - 2018
- [j1]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Hyperspectral Super-Resolution: A Coupled Tensor Factorization Approach. IEEE Trans. Signal Process. 66(24): 6503-6517 (2018) - [c4]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Hyperspectral Super-Resolution Via Coupled Tensor Factorization: Identifiability and Algorithms. ICASSP 2018: 3191-3195 - [c3]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Large-Scale Regularized Sumcor GCCA via Penalty-Dual Decomposition. ICASSP 2018: 6363-6367 - [c2]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma:
Hyperspectral Super-Resolution: Combining Low Rank Tensor and Matrix Structure. ICIP 2018: 3318-3322 - [i1]Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Mingyi Hong:
Structured SUMCOR Multiview Canonical Correlation Analysis for Large-Scale Data. CoRR abs/1804.08806 (2018) - 2015
- [c1]Charilaos I. Kanatsoulis, Nicholas D. Sidiropoulos:
Max-min feasible point pursuit for non-convex QCQP. ACSSC 2015: 401-405
Coauthor Index
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