Variational Feature Modeling
Variational Feature Modeling is a computational modeling paradigm within feature-based modeling that formally integrates probabilistic variations and uncertainties into the representation and manipulation of features, distinguishing it by its foundation in variational inference principles to enable robust, adaptive, and statistically grounded feature configurations.
15
Publications
535
Citations
59
Authors
26
Institutions
Publications per year
2017–2026
11
Parents
15
1–5 of 15
59
1
h-index
1
h-index
1
h-index
1
h-index
1
h-index
1–5 of 59
26

Xi'an Jiaotong University
Xi'an, China
2 h-index
11 publications
217 citations
Ningxia University
Yinchuan, China
1 h-index
6 publications
204 citations

Shenzhen University
Shenzhen, China
1 h-index
4 publications
236 citations
University of Kansas
Lawrence, United States
1 h-index
1 publications
19 citations
Stony Brook University
Stony Brook, United States
1 h-index
4 publications
284 citations

Hunan University
Changsha, China
1 h-index
3 publications
45 citations
Massachusetts Institute of Technology
Cambridge, United States
1 h-index
1 publications
26 citations
Ministry of Education of the People's Republic of China
Beijing, China
1 h-index
4 publications
168 citations
1–8 of 26
2 publications · 85 citations
2
h-index
Conference · 1 publications · 71 citations
1
h-index
Conference · 1 publications · 126 citations
1
h-index
1 publications · 25 citations
1
h-index
1 publications · 50 citations
1
h-index
1–5