Browsing by author "Deligiannis, Nikolaos"
Now showing items 21-40 of 58
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Designing recurrent neural networks by unfolding an l1-l1 minimization algorithm
Hung Le, Duy; Van Luong, Huynh; Deligiannis, Nikolaos (2019) -
ENTROPY-BASED FEATURE EXTRACTION FOR REAL-TIME SEMANTIC SEGMENTATION
Abrahamyan, Lusine; Deligiannis, Nikolaos (2022) -
Explaining Graph Neural Networks With Topology-Aware Node Selection: Application in Air Quality Inference
Rodrigo, Esther; Huu, Tien Do; Qin, Xuening; Hofman, Jelle; Panzica La Manna, Valerio; Philips, Wilfried; Deligiannis, Nikolaos (2022) -
Fake news detection using deep Markov random fields
Nguyen, Minh Duc; Huu, Tien Do; Calderbank, Robert; Deligiannis, Nikolaos (2019) -
Few-Shot Classification with Meta-Learning for Urban Infrastructure Monitoring Using Distributed Acoustic Sensing
Van Luong, Huynh; Deligiannis, Nikolaos; Wilhelm, Roman; Drapp, Bernd (2024) -
Fine-Grained Urban Air Quality Mapping from Sparse Mobile Air Pollution Measurements and Dense Traffic Density
Qin, Xuening; Huu, Tien Do; Hofman, Jelle; Rodrigo, Esther; Panzica La Manna, Valerio; Deligiannis, Nikolaos; Philips, Wilfried (2022) -
Generalization Error Bounds for Deep Unfolding RNNs
Joukovsky, Boris; Mukherjee, Tanmoy; Luong, Van Huynh; Deligiannis, Nikolaos (2021) -
Geometric matrix completion with deep conditional random fields
Nguyen, Duc Minh; Calderbank, Robert; Deligiannis, Nikolaos (2020) -
GRADIENT VARIANCE LOSS FOR STRUCTURE-ENHANCED IMAGE SUPER-RESOLUTION
Abrahamyan, Lusine; Truong, Anh Minh; Philips, Wilfried; Deligiannis, Nikolaos (2022) -
Graph auto-encoder for graph signal denoising
Huu, Tien Do; Nguyen, Minh Duc; Deligiannis, Nikolaos (2020) -
Graph convolutional neural networks with node transition probability-based message passing and DropNode regularization
Munteanu, Adrian; Huu, Tien Do; Nguyen, Minh Duc; Bekoulis, Ioannis; Deligiannis, Nikolaos (2021) -
Graph-deep-learning-based inference of fine-grained air quality from mobile IoT sensors
Do, Tien Huu; Tsiligianni, Evaggelia; Qin, Xuening; Hofman, Jelle; Panzica La Manna, Valerio; Philips, Wilfried; Deligiannis, Nikolaos (2020) -
HCGM-NET: A DEEP UNFOLDING NETWORK FOR FINANCIAL INDEX TRACKING
Pauwels, Ruben; Tsiligianni, Evaggelia; Deligiannis, Nikolaos (2021) -
Interpretable Deep Learning for Multimodal Super-Resolution of Medical Images
Tsiligianni, Evaggelia; Zerva, Matina; Marivani, Iman; Kondi, Lisimachos; Deligiannis, Nikolaos (2021) -
JOINT IMAGE SUPER-RESOLUTION VIA RECURRENT CONVOLUTIONAL NEURAL NETWORKS WITH COUPLED SPARSE PRIORS
Marivani, Iman; Tsiligianni, Evaggelia; Cornelis, Bruno; Deligiannis, Nikolaos (2020) -
Leaping Into Memories: Space-Time Deep Feature Synthesis
Stergiou, Alexandros; Deligiannis, Nikolaos (2023) -
Learned Gradient Compression for Distributed Deep Learning
Abrahamyan, Lusine; Chen, Yiming; Bekoulis, Ioannis; Deligiannis, Nikolaos (2022) -
Learned multimodal convolutional sparse coding for guided image super-resolution
Marivani, Iman; Tsiligianni, Evgennia; Cornelis, Bruno; Deligiannis, Nikolaos (2019) -
Matrix completion with variational graph autoencoders: Application in hyperlocal air quality inference
Huu, Tien Do; Nguyen, Minh Duc; Tsiligianni, Evgannia; Aguirre, A.L.; La Manna, V. P.; Pasveer, Frank; Philips, Wilfried; Deligiannis, Nikolaos (2019) -
Multimodal deep unfolding for guided image super-resolution
Marivani, Iman; Tsiligianni, Evangelia; Cornelis, Bruno; Deligiannis, Nikolaos (2020)