Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Bayesian conditional diffusion models for versatile spatiotemporal turbulence generation
Han Gao, Xu Han, Xiantao Fan, et al.
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 427, pp. 117023-117023
Open Access | Times Cited: 8

Showing 8 citing articles:

Using diffusion models for reducing spatiotemporal errors of deep learning based urban microclimate predictions at post-processing stage
Sepehrdad Tahmasebi, Geng Tian, Shaoxiang Qin, et al.
Physics of Fluids (2025) Vol. 37, Iss. 3
Closed Access | Times Cited: 1
Generative learning for forecasting the dynamics of high-dimensional complex systems
Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 4
Neural differentiable modeling with diffusion-based super-resolution for two-dimensional spatiotemporal turbulence
Xiantao Fan, Deepak Akhare, Jianxun Wang
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 433, pp. 117478-117478
Open Access | Times Cited: 4
Spatiotemporal modeling based on manifold learning for collision dynamic prediction of thin-walled structures under oblique load
Jian Xie, Junyuan Zhang, Hao Zhou, et al.
Computer Methods in Applied Mechanics and Engineering (2025) Vol. 440, pp. 117926-117926
Closed Access
Data-Driven Stochastic Closure Modeling via Conditional Diffusion Model and Neural Operator
Xinghao Dong, Chuanqi Chen, Jinlong Wu
Journal of Computational Physics (2025), pp. 114005-114005
Closed Access
Conditional neural field latent diffusion model for generating spatiotemporal turbulence
Pan Du, Meet Hemant Parikh, Xiantao Fan, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 2
Computational flow visualization to reveal hidden properties of complex flow with optical and computational methods
Jianqing Huang, Hecong Liu, Shuo Zhu, et al.
Cell Reports Physical Science (2024) Vol. 5, Iss. 11, pp. 102282-102282
Open Access | Times Cited: 1
Generative learning of the solution of parametric Partial Differential Equations using guided diffusion models and virtual observations
Han Gao, Sebastian Kaltenbach, Petros Koumoutsakos
Computer Methods in Applied Mechanics and Engineering (2024) Vol. 435, pp. 117654-117654
Closed Access | Times Cited: 1
Page 1

Scroll to top