45 citations · 98 across the 15 of their papers we have counts for
16 papers
New methods for modal decomposition in multi-mode fibres
S. Blin, T. Nguyen, D. Nguyen +9
We propose and demonstrate two methods for modal decomposition in multi-mode fibres. Linearly polarized modes propagating in a slightly multi-mode fibre are easily retrieved from i…
Neural Multigrid Memory For Computational Fluid Dynamics
Duc Minh Nguyen, Minh Chau Vu, Tuan Anh Nguyen +3
Turbulent flow simulation plays a crucial role in various applications, including aircraft and ship design, industrial process optimization, and weather prediction. In this paper,…
Toward Sustainable Transportation: Accelerating Vehicle Electrification with Dynamic Charging Deployment
Duc Minh Nguyen, Mustafa A. Kishk, Mohamed-Slim Alouini
Electric vehicles (EVs) are being actively adopted as a solution to sustainable transportation. However, a bottleneck remains with charging, where two of the main problems are the…
Responsive Regulation of Dynamic UAV Communication Networks Based on Deep Reinforcement Learning
Ran Zhang, Duc Minh, Nguyen +4
In this chapter, the regulation of Unmanned Aerial Vehicle (UAV) communication network is investigated in the presence of dynamic changes in the UAV lineup and user distribution. W…
Temporal Collaborative Filtering with Graph Convolutional Neural Networks
Esther Rodrigo Bonet, Duc Minh Nguyen, Nikos Deligiannis
Temporal collaborative filtering (TCF) methods aim at modelling non-static aspects behind recommender systems, such as the dynamics in users' preferences and social trends around i…
Modeling and Analysis of Dynamic Charging for EVs: A Stochastic Geometry Approach
Duc Minh Nguyen, Mustafa A. Kishk, Mohamed-Slim Alouini
With the increasing demand for greener and more energy efficient transportation solutions, electric vehicles (EVs) have emerged to be the future of transportation across the globe.…
Graph Convolutional Neural Networks with Node Transition Probability-based Message Passing and DropNode Regularization
Tien Huu Do, Duc Minh Nguyen, Giannis Bekoulis +2
Graph convolutional neural networks (GCNNs) have received much attention recently, owing to their capability in handling graph-structured data. Among the existing GCNNs, many metho…
Rumour Detection via News Propagation Dynamics and User Representation Learning
Tien Huu Do, Xiao Luo, Duc Minh Nguyen +1
Rumours have existed for a long time and have been known for serious consequences. The rapid growth of social media platforms has multiplied the negative impact of rumours; it thus…
Geometric Matrix Completion with Deep Conditional Random Fields
Duc Minh Nguyen, Robert Calderbank, Nikos Deligiannis
The problem of completing high-dimensional matrices from a limited set of observations arises in many big data applications, especially, recommender systems. Existing matrix comple…
Matrix Factorization via Deep Learning
Duc Minh Nguyen, Evaggelia Tsiligianni, Nikos Deligiannis
Matrix completion is one of the key problems in signal processing and machine learning. In recent years, deep-learning-based models have achieved state-of-the-art results in matrix…
Matrix Completion With Variational Graph Autoencoders: Application in Hyperlocal Air Quality Inference
Tien Huu Do, Duc Minh Nguyen, Evaggelia Tsiligianni +5
Inferring air quality from a limited number of observations is an essential task for monitoring and controlling air pollution. Existing inference methods typically use low spatial…
Regularizing Autoencoder-Based Matrix Completion Models via Manifold Learning
Duc Minh Nguyen, Evaggelia Tsiligianni, Robert Calderbank +1
Autoencoders are popular among neural-network-based matrix completion models due to their ability to retrieve potential latent factors from the partially observed matrices. Neverth…
Extendable Neural Matrix Completion
Duc Minh Nguyen, Evaggelia Tsiligianni, Nikos Deligiannis
Matrix completion is one of the key problems in signal processing and machine learning, with applications ranging from image pro- cessing and data gathering to classification and r…
Twitter User Geolocation using Deep Multiview Learning
Tien Huu Do, Duc Minh Nguyen, Evaggelia Tsiligianni +2
Predicting the geographical location of users on social networks like Twitter is an active research topic with plenty of methods proposed so far. Most of the existing work follows…
Multiview Deep Learning for Predicting Twitter Users' Location
Tien Huu Do, Duc Minh Nguyen, Evaggelia Tsiligianni +2
The problem of predicting the location of users on large social networks like Twitter has emerged from real-life applications such as social unrest detection and online marketing.…
Deep Learning Sparse Ternary Projections for Compressed Sensing of Images
Duc Minh Nguyen, Evaggelia Tsiligianni, Nikos Deligiannis
Compressed sensing (CS) is a sampling theory that allows reconstruction of sparse (or compressible) signals from an incomplete number of measurements, using of a sensing mechanism…