most citedManipulating solid-state spin concentration through charge transport

1 citations · 1 across the 4 of their papers we have counts for

collaborators

6 papers

cs.NI20241 cited

GLANCE: Graph-based Learnable Digital Twin for Communication Networks

Boning Li, Gunjan Verma, Timofey Efimov +2

As digital twins (DTs) to physical communication systems, network simulators can aid the design and deployment of communication networks. However, time-consuming simulations must b…

cs.GT2024

RL-CFR: Improving Action Abstraction for Imperfect Information Extensive-Form Games with Reinforcement Learning

Boning Li, Zhixuan Fang, Longbo Huang

Effective action abstraction is crucial in tackling challenges associated with large action spaces in Imperfect Information Extensive-Form Games (IIEFGs). However, due to the vast…

cs.SI2023

Deep Demixing: Reconstructing the Evolution of Network Epidemics

Boning Li, Gojko Čutura, Ananthram Swami +1

We propose the deep demixing (DDmix) model, a graph autoencoder that can reconstruct epidemics evolving over networks from partial or aggregated temporal information. Assuming know…

cs.NI2023

Learnable Digital Twin for Efficient Wireless Network Evaluation

Boning Li, Timofey Efimov, Abhishek Kumar +4

Network digital twins (NDTs) facilitate the estimation of key performance indicators (KPIs) before physically implementing a network, thereby enabling efficient optimization of the…

cs.LG2023

Hypergraphs with Edge-Dependent Vertex Weights: Spectral Clustering based on the 1-Laplacian

Yu Zhu, Boning Li, Santiago Segarra

We propose a flexible framework for defining the 1-Laplacian of a hypergraph that incorporates edge-dependent vertex weights. These weights are able to reflect varying importance o…

quant-ph20231 cited

Manipulating solid-state spin concentration through charge transport

Guoqing Wang, Changhao Li, Hao Tang +8

Solid-state spin defects are attractive candidates for developing quantum sensors and simulators. The spin and charge degrees of freedom in large defect ensembles are a promising p…