10 citations · 21 across the 8 of their papers we have counts for
8 papers
Efficient Multimodal Sampling via Tempered Distribution Flow
Yixuan Qiu, Xiao Wang
Sampling from high-dimensional distributions is a fundamental problem in statistical research and practice. However, great challenges emerge when the target density function is unn…
Learning Manifold Dimensions with Conditional Variational Autoencoders
Yijia Zheng, Tong He, Yixuan Qiu +1
Although the variational autoencoder (VAE) and its conditional extension (CVAE) are capable of state-of-the-art results across multiple domains, their precise behavior is still not…
Learning Multitask Gaussian Bayesian Networks
Shuai Liu, Yixuan Qiu, Baojuan Li +2
Major depressive disorder (MDD) requires study of brain functional connectivity alterations for patients, which can be uncovered by resting-state functional magnetic resonance imag…
Randomized spectral co-clustering for large-scale directed networks
Xiao Guo, Yixuan Qiu, Hai Zhang +1
Directed networks are broadly used to represent asymmetric relationships among units. Co-clustering aims to cluster the senders and receivers of directed networks simultaneously. I…
Stochastic Approximate Gradient Descent via the Langevin Algorithm
Yixuan Qiu, Xiao Wang
We introduce a novel and efficient algorithm called the stochastic approximate gradient descent (SAGD), as an alternative to the stochastic gradient descent for cases where unbiase…
Gradient-based Sparse Principal Component Analysis with Extensions to Online Learning
Yixuan Qiu, Jing Lei, Kathryn Roeder
Sparse principal component analysis (PCA) is an important technique for dimensionality reduction of high-dimensional data. However, most existing sparse PCA algorithms are based on…
Exact and efficient inference for Partial Bayes problems
Yixuan Qiu, Lingsong Zhang, Chuanhai Liu
Bayesian methods are useful for statistical inference. However, real-world problems can be challenging using Bayesian methods when the data analyst has only limited prior knowledge…
Finite-sample bounds for the multivariate Behrens-Fisher distribution with proportional covariances
Yixuan Qiu, Lingsong Zhang
The Behrens-Fisher problem is a well-known hypothesis testing problem in statistics concerning two-sample mean comparison. In this article, we confirm one conjecture in Eaton and O…