research
∙
08/17/2023
Uni-NLX: Unifying Textual Explanations for Vision and Vision-Language Tasks
Natural Language Explanations (NLE) aim at supplementing the prediction ...
share
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...
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...
research
∙
07/07/2022
Entropy-Based Feature Extraction For Real-Time Semantic Segmentation
This paper introduces an efficient patch-based computational module, coi...
research
∙
07/04/2022
Representation Learning with Information Theory for COVID-19 Detection
Successful data representation is a fundamental factor in machine learni...
research
∙
06/20/2022
Visualizing and Understanding Self-Supervised Vision Learning
Self-Supervised vision learning has revolutionized deep learning, becomi...
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...
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...
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...
research
∙
07/23/2021
Bias Loss for Mobile Neural Networks
Compact convolutional neural networks (CNNs) have witnessed exceptional ...
research
∙
03/16/2021
Learned Gradient Compression for Distributed Deep Learning
Training deep neural networks on large datasets containing high-dimensio...
research
∙
10/13/2020
Temporal Collaborative Filtering with Graph Convolutional Neural Networks
Temporal collaborative filtering (TCF) methods aim at modelling non-stat...
research
∙
10/06/2020
Fact Extraction and VERification – The FEVER case: An Overview
Fact Extraction and VERification (FEVER) is a recently introduced task w...
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...
research
∙
09/07/2020
Interpretable Deep Multimodal Image Super-Resolution
Multimodal image super-resolution (SR) is the reconstruction of a high r...
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...
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...
research
∙
01/21/2020
Multimodal Deep Unfolding for Guided Image Super-Resolution
The reconstruction of a high resolution image given a low resolution obs...
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...
research
∙
10/18/2019
Multimodal Image Super-resolution via Deep Unfolding with Side Information
Deep learning methods have been successfully applied to various computer...
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 ...
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...
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...
research
∙
01/29/2019
Geometric Matrix Completion with Deep Conditional Random Fields
The problem of completing high-dimensional matrices from a limited set o...
research
∙
12/04/2018
Matrix Factorization via Deep Learning
Matrix completion is one of the key problems in signal processing and ma...
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...
research
∙
07/04/2018
Regularizing Autoencoder-Based Matrix Completion Models via Manifold Learning
Autoencoders are popular among neural-network-based matrix completion mo...
research
∙
05/13/2018
Extendable Neural Matrix Completion
Matrix completion is one of the key problems in signal processing and ma...
research
∙
05/11/2018
Twitter User Geolocation using Deep Multiview Learning
Predicting the geographical location of users on social networks like Tw...
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...
research
∙
12/21/2017
Multiview Deep Learning for Predicting Twitter Users' Location
The problem of predicting the location of users on large social networks...
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...
research
∙
08/28/2017
Deep Learning Sparse Ternary Projections for Compressed Sensing of Images
Compressed sensing (CS) is a sampling theory that allows reconstruction ...
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...
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...
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...
research
∙
09/13/2015
Vectors of Locally Aggregated Centers for Compact Video Representation
We propose a novel vector aggregation technique for compact video repres...
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...
research
∙
10/10/2014
