LD-CSNet: A latent diffusion-based architecture for perceptual Compressed Sensing
B Zheng, G Sun, L Dong, S Wang - Neural Networks, 2024 - Elsevier
Compressed Sensing (CS) is a groundbreaking paradigm in image acquisition, challenging
the constraints of the Nyquist–Shannon sampling theorem. This enables high-quality image …
the constraints of the Nyquist–Shannon sampling theorem. This enables high-quality image …
Near-optimal Steiner tree computation powered by node embeddings
B Yang, W Zheng - Knowledge and Information Systems, 2023 - Springer
Steiner minimum tree problem on a graph, ie, finding a tree with the minimum weight that
covers the set of terminal nodes, is a classical NP-hard problem. Thus, we develop a method …
covers the set of terminal nodes, is a classical NP-hard problem. Thus, we develop a method …
Distributed Compressed Sensing With Personalized Variational Auto-Encoders
This paper proposes an efficient distributed learning algorithm for compressed sensing
recovery over a multi-sensor network, by exploiting the personalization technique to capture …
recovery over a multi-sensor network, by exploiting the personalization technique to capture …
Generative compressed sensing with Fourier measurements
M Scott - 2023 - open.library.ubc.ca
Abstract In~\cite {bora2017compressed}, a mathematical framework was developed for
compressed sensing guarantees in the setting where the measurement matrix is Gaussian …
compressed sensing guarantees in the setting where the measurement matrix is Gaussian …