Nikos Deligiannis

research

∙ 08/17/2023

Uni-NLX: Unifying Textual Explanations for Vision and Vision-Language Tasks

Natural Language Explanations (NLE) aim at supplementing the prediction ...

0 Fawaz Sammani, et al. ∙

research

∙ 06/18/2023

The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data

Challenges drive the state-of-the-art of automated medical image analysi...

0 Luuk H. Boulogne, et al. ∙

research

∙ 03/17/2023

Leaping Into Memories: Space-Time Deep Feature Synthesis

The success of deep learning models has led to their adaptation and adop...

0 Alexandros Stergiou, et al. ∙

research

∙ 07/07/2022

Entropy-Based Feature Extraction For Real-Time Semantic Segmentation

This paper introduces an efficient patch-based computational module, coi...

0 Lusine Abrahamyan, et al. ∙

research

∙ 07/04/2022

Representation Learning with Information Theory for COVID-19 Detection

Successful data representation is a fundamental factor in machine learni...

11 Abel Díaz Berenguer, et al. ∙

research

∙ 06/20/2022

Visualizing and Understanding Self-Supervised Vision Learning

Self-Supervised vision learning has revolutionized deep learning, becomi...

263 Fawaz Sammani, et al. ∙

research

∙ 03/09/2022

NLX-GPT: A Model for Natural Language Explanations in Vision and Vision-Language Tasks

Natural language explanation (NLE) models aim at explaining the decision...

30 Fawaz Sammani, et al. ∙

research

∙ 02/02/2022

Gradient Variance Loss for Structure-Enhanced Image Super-Resolution

Recent success in the field of single image super-resolution (SISR) is a...

0 Lusine Abrahamyan, et al. ∙

research

∙ 09/13/2021

Traffic Event Detection as a Slot Filling Problem

In this paper, we introduce the new problem of extracting fine-grained t...

0 Xiangyu Yang, et al. ∙

research

∙ 07/23/2021

Bias Loss for Mobile Neural Networks

Compact convolutional neural networks (CNNs) have witnessed exceptional ...

0 Lusine Abrahamyan, et al. ∙

research

∙ 03/16/2021

Learned Gradient Compression for Distributed Deep Learning

Training deep neural networks on large datasets containing high-dimensio...

0 Lusine Abrahamyan, et al. ∙

research

∙ 10/13/2020

Temporal Collaborative Filtering with Graph Convolutional Neural Networks

Temporal collaborative filtering (TCF) methods aim at modelling non-stat...

0 Esther Rodrigo Bonet, et al. ∙

research

∙ 10/06/2020

Fact Extraction and VERification – The FEVER case: An Overview

Fact Extraction and VERification (FEVER) is a recently introduced task w...

0 Giannis Bekoulis, et al. ∙

research

∙ 10/02/2020

A Deep-Unfolded Reference-Based RPCA Network For Video Foreground-Background Separation

Deep unfolded neural networks are designed by unrolling the iterations o...

0 Huynh Van Luong, et al. ∙

research

∙ 09/07/2020

Interpretable Deep Multimodal Image Super-Resolution

Multimodal image super-resolution (SR) is the reconstruction of a high r...

0 Iman Marivani, et al. ∙

research

∙ 08/28/2020

Graph Convolutional Neural Networks with Node Transition Probability-based Message Passing and DropNode Regularization

Graph convolutional neural networks (GCNNs) have received much attention...

0 Tien Huu Do, et al. ∙

research

∙ 03/18/2020

Interpretable Deep Recurrent Neural Networks via Unfolding Reweighted ℓ_1-ℓ_1 Minimization: Architecture Design and Generalization Analysis

Deep unfolding methods—for example, the learned iterative shrinkage thre...

0 Huynh Van Luong, et al. ∙

research

∙ 01/21/2020

Multimodal Deep Unfolding for Guided Image Super-Resolution

The reconstruction of a high resolution image given a low resolution obs...

16 Iman Marivani, et al. ∙

research

∙ 12/02/2019

DeepFPC: Deep Unfolding of a Fixed-Point Continuation Algorithm for Sparse Signal Recovery from Quantized Measurements

We present DeepFPC, a novel deep neural network designed by unfolding th...

0 Peng Xiao, et al. ∙

research

∙ 10/18/2019

Multimodal Image Super-resolution via Deep Unfolding with Side Information

Deep learning methods have been successfully applied to various computer...

0 Iman Marivani, et al. ∙

research

∙ 07/04/2019

Deep Coupled-Representation Learning for Sparse Linear Inverse Problems with Side Information

In linear inverse problems, the goal is to recover a target signal from ...

0 Evaggelia Tsiligianni, et al. ∙

research

∙ 04/18/2019

Rumour Detection via News Propagation Dynamics and User Representation Learning

Rumours have existed for a long time and have been known for serious con...

0 Tien Huu Do, et al. ∙

research

∙ 02/18/2019

Designing recurrent neural networks by unfolding an l1-l1 minimization algorithm

We propose a new deep recurrent neural network (RNN) architecture for se...

0 Hung Duy Le, et al. ∙

research

∙ 01/29/2019

Geometric Matrix Completion with Deep Conditional Random Fields

The problem of completing high-dimensional matrices from a limited set o...

8 Duc Minh Nguyen, et al. ∙

research

∙ 12/04/2018

Matrix Factorization via Deep Learning

Matrix completion is one of the key problems in signal processing and ma...

0 Duc Minh Nguyen, et al. ∙

research

∙ 11/05/2018

Matrix Completion With Variational Graph Autoencoders: Application in Hyperlocal Air Quality Inference

Inferring air quality from a limited number of observations is an essent...

0 Tien Huu Do, et al. ∙

research

∙ 07/04/2018

Regularizing Autoencoder-Based Matrix Completion Models via Manifold Learning

Autoencoders are popular among neural-network-based matrix completion mo...

0 Duc Minh Nguyen, et al. ∙

research

∙ 05/13/2018

Extendable Neural Matrix Completion

Matrix completion is one of the key problems in signal processing and ma...

0 Duc Minh Nguyen, et al. ∙

research

∙ 05/11/2018

Twitter User Geolocation using Deep Multiview Learning

Predicting the geographical location of users on social networks like Tw...

0 Tien Huu Do, et al. ∙

research

∙ 02/08/2018

Online Decomposition of Compressive Streaming Data Using n-ℓ_1 Cluster-Weighted Minimization

We consider a decomposition method for compressive streaming data in the...

0 Huynh Van Luong, et al. ∙

research

∙ 12/21/2017

Multiview Deep Learning for Predicting Twitter Users' Location

The problem of predicting the location of users on large social networks...

0 Tien Huu Do, et al. ∙

research

∙ 09/25/2017

Multimodal Image Super-Resolution via Joint Sparse Representations induced by Coupled Dictionaries

Real-world data processing problems often involve various image modaliti...

0 Pingfan Song, et al. ∙

research

∙ 08/28/2017

Deep Learning Sparse Ternary Projections for Compressed Sensing of Images

Compressed sensing (CS) is a sampling theory that allows reconstruction ...

0 Duc Minh Nguyen, et al. ∙

research

∙ 01/24/2017

Incorporating Prior Information in Compressive Online Robust Principal Component Analysis

We consider an online version of the robust Principle Component Analysis...

0 Huynh Van Luong, et al. ∙

research

∙ 07/14/2016

Multi-modal dictionary learning for image separation with application in art investigation

In support of art investigation, we propose a new source separation meth...

0 Nikos Deligiannis, et al. ∙

research

∙ 05/20/2016

X-ray image separation via coupled dictionary learning

In support of art investigation, we propose a new source sepa- ration me...

0 Nikos Deligiannis, et al. ∙

research

∙ 09/13/2015

Vectors of Locally Aggregated Centers for Compact Video Representation

We propose a novel vector aggregation technique for compact video repres...

0 Alhabib Abbas, et al. ∙

research

∙ 03/11/2015

Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Background Subtraction

We propose and analyze an online algorithm for reconstructing a sequence...

0 João F. C. Mota, et al. ∙

research

∙ 10/10/2014

Compressed Sensing With Side Information: Geometrical Interpretation and Performance Bounds

We address the problem of Compressed Sensing (CS) with side information....

0 João F. C. Mota, et al. ∙

Nikos Deligiannis

Featured Co-authors