
Temporal Collaborative Filtering with Graph Convolutional Neural Networks
Temporal collaborative filtering (TCF) methods aim at modelling nonstat...
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Fact Extraction and VERification – The FEVER case: An Overview
Fact Extraction and VERification (FEVER) is a recently introduced task w...
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A DeepUnfolded ReferenceBased RPCA Network For Video ForegroundBackground Separation
Deep unfolded neural networks are designed by unrolling the iterations o...
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Interpretable Deep Multimodal Image SuperResolution
Multimodal image superresolution (SR) is the reconstruction of a high r...
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Graph Convolutional Neural Networks with Node Transition Probabilitybased Message Passing and DropNode Regularization
Graph convolutional neural networks (GCNNs) have received much attention...
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Interpretable Deep Recurrent Neural Networks via Unfolding Reweighted ℓ_1ℓ_1 Minimization: Architecture Design and Generalization Analysis
Deep unfolding methods—for example, the learned iterative shrinkage thre...
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Multimodal Deep Unfolding for Guided Image SuperResolution
The reconstruction of a high resolution image given a low resolution obs...
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DeepFPC: Deep Unfolding of a FixedPoint Continuation Algorithm for Sparse Signal Recovery from Quantized Measurements
We present DeepFPC, a novel deep neural network designed by unfolding th...
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Multimodal Image Superresolution via Deep Unfolding with Side Information
Deep learning methods have been successfully applied to various computer...
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Deep CoupledRepresentation Learning for Sparse Linear Inverse Problems with Side Information
In linear inverse problems, the goal is to recover a target signal from ...
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Rumour Detection via News Propagation Dynamics and User Representation Learning
Rumours have existed for a long time and have been known for serious con...
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Designing recurrent neural networks by unfolding an l1l1 minimization algorithm
We propose a new deep recurrent neural network (RNN) architecture for se...
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Geometric Matrix Completion with Deep Conditional Random Fields
The problem of completing highdimensional matrices from a limited set o...
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Matrix Factorization via Deep Learning
Matrix completion is one of the key problems in signal processing and ma...
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Matrix Completion With Variational Graph Autoencoders: Application in Hyperlocal Air Quality Inference
Inferring air quality from a limited number of observations is an essent...
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Regularizing AutoencoderBased Matrix Completion Models via Manifold Learning
Autoencoders are popular among neuralnetworkbased matrix completion mo...
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Extendable Neural Matrix Completion
Matrix completion is one of the key problems in signal processing and ma...
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Twitter User Geolocation using Deep Multiview Learning
Predicting the geographical location of users on social networks like Tw...
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Online Decomposition of Compressive Streaming Data Using nℓ_1 ClusterWeighted Minimization
We consider a decomposition method for compressive streaming data in the...
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Multiview Deep Learning for Predicting Twitter Users' Location
The problem of predicting the location of users on large social networks...
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Multimodal Image SuperResolution via Joint Sparse Representations induced by Coupled Dictionaries
Realworld data processing problems often involve various image modaliti...
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Deep Learning Sparse Ternary Projections for Compressed Sensing of Images
Compressed sensing (CS) is a sampling theory that allows reconstruction ...
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Incorporating Prior Information in Compressive Online Robust Principal Component Analysis
We consider an online version of the robust Principle Component Analysis...
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Multimodal dictionary learning for image separation with application in art investigation
In support of art investigation, we propose a new source separation meth...
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Xray image separation via coupled dictionary learning
In support of art investigation, we propose a new source sepa ration me...
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Vectors of Locally Aggregated Centers for Compact Video Representation
We propose a novel vector aggregation technique for compact video repres...
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AdaptiveRate Sparse Signal Reconstruction With Application in Compressive Background Subtraction
We propose and analyze an online algorithm for reconstructing a sequence...
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Compressed Sensing With Side Information: Geometrical Interpretation and Performance Bounds
We address the problem of Compressed Sensing (CS) with side information....
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Nikos Deligiannis
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