31 citations · 33 across the 9 of their papers we have counts for
11 papers
EMPURPLE: A Free Lunch for Diffusion Distillation based on the Information Bottleneck
Zilai Li, Lujia Bai
Diffusion models achieve impressive image-generation quality but remain expensive at inference time. Diffusion distillation reduces sampling steps, yet many distilled models, inclu…
Validating spatial-temporal separability for stationary processes
Lujia Bai, Holger Dette, Zihao Yuan
A crucial assumption to reduce computational complexity in spatial-temporal data analysis is separability, which factors the covariance structure into a purely spatial and a purely…
Asymptotic Uniform False Discovery Rate Control for Inference of Time-varying Correlations
Bufan Li, Lujia Bai, Weichi Wu
Inference for locally stationary time series is challenging because the associated hypotheses form an uncountable collection over a continuous time interval, making pointwise false…
Measuring deviations from spherical symmetry
Lujia Bai, Holger Dette
Most of the work on checking spherical symmetry assumptions on the distribution of the -dimensional random vector has its focus on statistical tests for the null hypothesis…
F-scheduler: illuminating the free-lunch design space for fast sampling of diffusion models
Zilai Li, Lujia Bai
Diffusion models are the state-of-the-art generative models for high-resolution images, but sampling from pretrained models is computationally expensive, motivating interest in fas…
A portmanteau test for multivariate non-stationary functional time series with an increasing number of lags
Lujia Bai, Holger Dette, Weichi Wu
Multivariate locally stationary functional time series provide a flexible framework for modeling functional data exhibiting both temporal and spatial dependencies while allowing fo…
Complex trend inference for high-dimensional piecewise locally stationary time series
Lujia Bai, David Veitch, Weichi Wu +2
This paper studies high-dimensional trend inference for piecewise smooth signals under nonstationary noise and asynchronous structural breaks by first detecting asynchronous change…
Difference-based covariance matrix estimate in time series nonparametric regression with applications to specification tests
Lujia Bai, Weichi Wu
Long-run covariance matrix estimation is the building block of time series inference. The corresponding difference-based estimator, which avoids detrending, has attracted considera…
Time-varying correlation network analysis of non-stationary multivariate time series with complex trends
Lujia Bai, Weichi Wu
This paper proposes a flexible framework for inferring large-scale time-varying and time-lagged correlation networks from multivariate or high-dimensional non-stationary time serie…
UniPC: A Unified Predictor-Corrector Framework for Fast Sampling of Diffusion Models
Wenliang Zhao, Lujia Bai, Yongming Rao +2
Diffusion probabilistic models (DPMs) have demonstrated a very promising ability in high-resolution image synthesis. However, sampling from a pre-trained DPM is time-consuming due…
Detecting long-range dependence for time-varying linear models
Lujia Bai, Weichi Wu
We consider the problem of testing for long-range dependence in time-varying coefficient regression models, where the covariates and errors are locally stationary, allowing complex…