Implicit neural networks have demonstrated remarkable success in various...
Denoising diffusion models have shown outstanding performance in image
e...
Human activity recognition (HAR) with wearables is promising research th...
It is a challenging problem to detect and recognize targets on complex
l...
Semi-supervised learning acts as an effective way to leverage massive
un...
Digital twin (DT) is one of the most promising enabling technologies for...
This paper addresses the asymptotic behavior of a particular type of
inf...
In this paper, we propose to disentangle and interpret contextual effect...
In the past decade, sparse and low-rank recovery have drawn much attenti...
We revisit the initialization of deep residual networks (ResNets) by
int...
Synchronized measurements of a large power grid enable an unprecedented
...
The location of broken insulators in aerial images is a challenging task...
Invisible units refer mainly to small-scale units that are not monitored...
This work addresses the issue of large covariance matrix estimation in
h...
Spectrum sensing is a fundamental problem in cognitive radio. We propose...
Kernel method is a very powerful tool in machine learning. The trick of
...