4 papers · 1 filter
Gaussian mixture layers for neural networks
Sinho Chewi, Philippe Rigollet, Yuling Yan
The mean-field theory for two-layer neural networks considers infinitely wide networks that are linearly parameterized by a probability measure over the parameter space. This nonpa…
O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions
Gen Li, Yuling Yan
Score-based diffusion models, which generate new data by learning to reverse a diffusion process that perturbs data from the target distribution into noise, have achieved remarkabl…
Adapting to Unknown Low-Dimensional Structures in Score-Based Diffusion Models
Gen Li, Yuling Yan
This paper investigates score-based diffusion models when the underlying target distribution is concentrated on or near low-dimensional manifolds within the higher-dimensional spac…
A Score-Based Density Formula, with Applications in Diffusion Generative Models
Gen Li, Yuling Yan
Score-based generative models (SGMs) have revolutionized the field of generative modeling, achieving unprecedented success in generating realistic and diverse content. Despite empi…