1 citations · 2 across the 7 of their papers we have counts for
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How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff +1
Discrete diffusion models have gained increasing attention for their ability to model complex distributions with tractable sampling and inference. However, the error analysis for d…
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity
Haoxuan Chen, Yinuo Ren, Lexing Ying +1
Diffusion models have become a leading method for generative modeling of both image and scientific data. As these models are costly to train and \emph{evaluate}, reducing the infer…
A sublinear-time randomized algorithm for column and row subset selection based on strong rank-revealing QR factorizations
Alice Cortinovis, Lexing Ying
In this work, we analyze a sublinear-time algorithm for selecting a few rows and columns of a matrix for low-rank approximation purposes. The algorithm is based on an initial unifo…
Convergence Analysis of Discrete Diffusion Model: Exact Implementation through Uniformization
Hongrui Chen, Lexing Ying
Diffusion models have achieved huge empirical success in data generation tasks. Recently, some efforts have been made to adapt the framework of diffusion models to discrete state s…
Interacting Annealed Importance Sampling via Population-Based MCMC Kernels
Haoxuan Chen, Lexing Ying
Sampling from a multimodal distribution is a fundamental and challenging problem in computational science and statistics. Among various approaches proposed for this task, one popul…