1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.AI2024
Enhancing Topic Interpretability for Neural Topic Modeling through Topic-wise Contrastive Learning
Xin Gao, Yang Lin, Ruiqing Li +4
Data mining and knowledge discovery are essential aspects of extracting valuable insights from vast datasets. Neural topic models (NTMs) have emerged as a valuable unsupervised too…
physics.flu-dyn2024★ 1 cited
Data-driven methods for flow and transport in porous media: a review
Guang Yang, Ran Xu, Yusong Tian +3
This review examined the current advancements in data-driven methods for analyzing flow and transport in porous media, which has various applications in energy, chemical engineerin…
physics.flu-dyn2024
An investigation of anisotropy in the bubbly turbulent flow via direct numerical simulations
Xuanwei Zhang, Yanchao Liu, Wenkang Wang +2
This study explores the dynamics of dispersed bubbly turbulent flow in a channel using interface-resolved direct numerical simulation (DNS) with an efficient Coupled Level-Set Volu…