98 citations · 292 across the 29 of their papers we have counts for
11 papers · 1 filter
The Bayesian Committee Approach for Computational Physics Problems
Li Chen, Xiao Liang, Hui Zhai
In this work, we propose a method for efficient learning of a multi-dimensional function. This method combines the Bayesian neural networks and the query-by-committee method. A com…
Impact and Calibration of Nonlinear Reciprocity Mismatch in Massive MIMO
Rongjiang Nie, Li Chen, Nan Zhao +3
Time-division-duplexing massive multiple-input multiple-output (MIMO) systems estimate the channel state information (CSI) by leveraging the uplink-downlink channel reciprocity, wh…
RS-MetaNet: Deep meta metric learning for few-shot remote sensing scene classification
Haifeng Li, Zhenqi Cui, Zhiqing Zhu +4
Training a modern deep neural network on massive labeled samples is the main paradigm in solving the scene classification problem for remote sensing, but learning from only a few d…
Generative Model without Prior Distribution Matching
Cong Geng, Jia Wang, Li Chen +1
Variational Autoencoder (VAE) and its variations are classic generative models by learning a low-dimensional latent representation to satisfy some prior distribution (e.g., Gaussia…
Composite Signalling for DFRC: Dedicated Probing Signal or Not?
Li Chen, Fan Liu, Jun Liu +1
Dual-functional radar-communication (DFRC) is a promising new solution to simultaneously probe the radar target and transmit information in wireless networks. In this paper, we stu…
Simulating Unknown Target Models for Query-Efficient Black-box Attacks
Chen Ma, Li Chen, Jun-Hai Yong
Many adversarial attacks have been proposed to investigate the security issues of deep neural networks. In the black-box setting, current model stealing attacks train a substitute…