Turbulent flow simulation plays a crucial role in various applications,
...
Electric vehicles (EVs) are being actively adopted as a solution to
sust...
Temporal collaborative filtering (TCF) methods aim at modelling non-stat...
With the increasing demand for greener and more energy efficient
transpo...
Graph convolutional neural networks (GCNNs) have received much attention...
Rumours have existed for a long time and have been known for serious
con...
The problem of completing high-dimensional matrices from a limited set o...
Matrix completion is one of the key problems in signal processing and ma...
Inferring air quality from a limited number of observations is an essent...
Autoencoders are popular among neural-network-based matrix completion mo...
Matrix completion is one of the key problems in signal processing and ma...
Predicting the geographical location of users on social networks like Tw...
The problem of predicting the location of users on large social networks...
Compressed sensing (CS) is a sampling theory that allows reconstruction ...