5 citations · 6 across the 4 of their papers we have counts for
4 papers
Leveraging Multimodal Diffusion Models to Accelerate Imaging with Side Information
Timofey Efimov, Harry Dong, Megna Shah +3
Diffusion models have found phenomenal success as expressive priors for solving inverse problems, but their extension beyond natural images to more structured scientific domains re…
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…
Accelerating Convergence of Score-Based Diffusion Models, Provably
Gen Li, Yu Huang, Timofey Efimov +3
Score-based diffusion models, while achieving remarkable empirical performance, often suffer from low sampling speed, due to extensive function evaluations needed during the sampli…
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…