Zobrazeno 1 - 10
of 156
pro vyhledávání: '"Qiu, Yixuan"'
Generative models based on latent variables, such as generative adversarial networks (GANs) and variational auto-encoders (VAEs), have gained lots of interests due to their impressive performance in many fields. However, many data such as natural ima
Externí odkaz:
http://arxiv.org/abs/2409.18374
In this paper, the network equations calculation of $^{187}$Re-$^{187}$Os clock-related nuclide abundance in s-process is studied, and the sensitivities of Maxwellian-Averaged neutron capture cross sections for each nuclide are analyzed in detail. Fi
Externí odkaz:
http://arxiv.org/abs/2409.02704
Bilevel optimization refers to scenarios whereby the optimal solution of a lower-level energy function serves as input features to an upper-level objective of interest. These optimal features typically depend on tunable parameters of the lower-level
Externí odkaz:
http://arxiv.org/abs/2403.04763
Autor:
Qiu, Yixuan, Wang, Xiao
Sampling from high-dimensional distributions is a fundamental problem in statistical research and practice. However, great challenges emerge when the target density function is unnormalized and contains isolated modes. We tackle this difficulty by fi
Externí odkaz:
http://arxiv.org/abs/2304.03933
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 fully understood, particularly in the context of data (like images) t
Externí odkaz:
http://arxiv.org/abs/2302.11756
Major depressive disorder (MDD) requires study of brain functional connectivity alterations for patients, which can be uncovered by resting-state functional magnetic resonance imaging (rs-fMRI) data. We consider the problem of identifying alterations
Externí odkaz:
http://arxiv.org/abs/2205.05343
Publikováno v:
In Expert Systems With Applications 10 December 2024 257
Directed networks are broadly used to represent asymmetric relationships among units. Co-clustering aims to cluster the senders and receivers of directed networks simultaneously. In particular, the well-known spectral clustering algorithm could be mo
Externí odkaz:
http://arxiv.org/abs/2004.12164
Autor:
Qiu, Yixuan, Wang, Xiao
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 unbiased stochastic gradients cannot be trivially obtained. Traditional metho
Externí odkaz:
http://arxiv.org/abs/2002.05519
Autor:
Li, Hui, Qiu, Yixuan, Gao, Di, Wang, Youlin, Zhou, Tianxiang, Gao, Tianwei, Xie, Zhengyang, Xu, Kang, Yu, Pengfei
Publikováno v:
In FlatChem September 2023 41