53 citations · 69 across the 5 of their papers we have counts for
8 papers
On Fast Sampling of Diffusion Probabilistic Models
Zhifeng Kong, Wei Ping
In this work, we propose FastDPM, a unified framework for fast sampling in diffusion probabilistic models. FastDPM generalizes previous methods and gives rise to new algorithms wit…
Universal Approximation of Residual Flows in Maximum Mean Discrepancy
Zhifeng Kong, Kamalika Chaudhuri
Normalizing flows are a class of flexible deep generative models that offer easy likelihood computation. Despite their empirical success, there is little theoretical understanding…
DiffWave: A Versatile Diffusion Model for Audio Synthesis
Zhifeng Kong, Wei Ping, Jiaji Huang +2
In this work, we propose DiffWave, a versatile diffusion probabilistic model for conditional and unconditional waveform generation. The model is non-autoregressive, and converts th…
The Expressive Power of a Class of Normalizing Flow Models
Zhifeng Kong, Kamalika Chaudhuri
Normalizing flows have received a great deal of recent attention as they allow flexible generative modeling as well as easy likelihood computation. While a wide variety of flow mod…
Fastened CROWN: Tightened Neural Network Robustness Certificates
Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong +3
The rapid growth of deep learning applications in real life is accompanied by severe safety concerns. To mitigate this uneasy phenomenon, much research has been done providing reli…
Convergence Analysis of the Dynamics of a Special Kind of Two-Layered Neural Networks with and Regularization
Zhifeng Kong
In this paper, we made an extension to the convergence analysis of the dynamics of two-layered bias-free networks with one output. We took into consideration two popular reg…