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An effective one-iteration learning algorithm based on Gaussian mixture expansion for densities Journal article
Lu, Weiguo, Wu, Xuan, Ding, Deng, Yuan, Gangnan, Zhuang, Jirong. An effective one-iteration learning algorithm based on Gaussian mixture expansion for densities[J]. Communications in Nonlinear Science and Numerical Simulation, 2025, 142, 108494.
Authors:  Lu, Weiguo;  Wu, Xuan;  Ding, Deng;  Yuan, Gangnan;  Zhuang, Jirong
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:3.4/3.3 | Submit date：2025/01/22
Gaussian Mixture Model  Density Approximation  Neural Network  Expectation Maximization  Inverse Problem  Embedding  
Diffusion model conditioning on Gaussian mixture model and negative Gaussian mixture gradient Journal article
Lu, Weiguo, Wu, Xuan, Ding, Deng, Duan, Jinqiao, Zhuang, Jirong, Yuan, Gangnan. Diffusion model conditioning on Gaussian mixture model and negative Gaussian mixture gradient[J]. Neurocomputing, 2025, 614, 128764.
Authors:  Lu, Weiguo;  Wu, Xuan;  Ding, Deng;  Duan, Jinqiao;  Zhuang, Jirong; et al.
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:5.5/5.5 | Submit date：2025/01/22
Diffusion Model  Gaussian Mixture Model  Latent Variable  Neural Network  Wasserstein Distance  
A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-Dimensional American Options Journal article
Zhuang, Jirong, Ding, Deng, Lu, Weiguo, Wu, Xuan, Yuan, Gangnan. A Gaussian Process Based Method with Deep Kernel Learning for Pricing High-Dimensional American Options[J]. Computational Economics, 2025.
Authors:  Zhuang, Jirong;  Ding, Deng;  Lu, Weiguo;  Wu, Xuan;  Yuan, Gangnan
Favorite | TC[WOS]:0 TC[Scopus]:0  IF:1.9/1.8 | Submit date：2025/01/22
Deep Kernel Learning  Gaussian Process  High-dimensional American Option  Machine Learning  Regression Based Monte Carlo Method