82 citations · 246 across the 24 of their papers we have counts for
4 papers · 1 filter
Quantized Compressed Sensing with Score-based Generative Models
Xiangming Meng, Yoshiyuki Kabashima
We consider the general problem of recovering a high-dimensional signal from noisy quantized measurements. Quantization, especially coarse quantization such as 1-bit sign measureme…
Diffusion Model Based Posterior Sampling for Noisy Linear Inverse Problems
Xiangming Meng, Yoshiyuki Kabashima
With the rapid development of diffusion models and flow-based generative models, there has been a surge of interests in solving noisy linear inverse problems, e.g., super-resolutio…
A Unitary Transform Based Generalized Approximate Message Passing
Jiang Zhu, Xiangming Meng, Xupeng Lei +1
We consider the problem of recovering an unknown signal from general nonlinear measurements obtained through a generalized linear model (GLM), i.e.,…
Stochastic Neural Networks with Infinite Width are Deterministic
Liu Ziyin, Hanlin Zhang, Xiangming Meng +3
This work theoretically studies stochastic neural networks, a main type of neural network in use. We prove that as the width of an optimized stochastic neural network tends to infi…