most citedA comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

701 citations · 709 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IT2023

Channel Cycle Time: A New Measure of Short-term Fairness

Pengfei Shen, Yulin Shao, Haoyuan Pan +2

This paper puts forth a new metric, dubbed channel cycle time (CCT), to measure the short-term fairness of communication networks. CCT characterizes the average duration between tw…

cs.IT2022

Phase Code Discovery for Pulse Compression Radar: A Genetic Algorithm Approach

Xinyan Xie, Runxin Zhang, Yulin Shao +1

Discovering sequences with desired properties has long been an interesting intellectual pursuit. In pulse compression radar (PCR), discovering phase codes with low aperiodic autoco…

physics.comp-ph2022★ 701 cited

A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

Chenxi Wu, Min Zhu, Qinyang Tan +2

Physics-informed neural networks (PINNs) have shown to be an effective tool for solving forward and inverse problems of partial differential equations (PDEs). PINNs embed the PDEs…

cs.IT2022★ 2 cited

Dynamic gNodeB Sleep Control for Energy-Conserving 5G Radio Access Network

Pengfei Shen, Yulin Shao, Qi Cao +1

5G radio access network (RAN) is consuming much more energy than legacy RAN due to the denser deployments of gNodeBs (gNBs) and higher single-gNB power consumption. In an effort to…

cs.DB2022★ 6 cited

Sampling-based Estimation of the Number of Distinct Values in Distributed Environment

Jiajun Li, Zhewei Wei, Bolin Ding +3

In data mining, estimating the number of distinct values (NDV) is a fundamental problem with various applications. Existing methods for estimating NDV can be broadly classified int…

cs.NI2022

Digital Twin for Networking: A Data-driven Performance Modeling Perspective

Linbo Hui, Mowei Wang, Liang Zhang +2

Emerging technologies and applications make the network unprecedentedly complex and heterogeneous, leading physical network practices to be costly and risky. The digital twin netwo…