Inferring temporal dynamics from cross-sectional data using Langevin dynamics

• المؤلفون الرئيسيون: Dutta, Pritha, Quax, Rick, Crielaard, Loes, Badiali, Luca, Sloot, Peter M. A.
• مؤلفون آخرون: Interdisciplinary Graduate School (IGS)
• التنسيق: مقال
• اللغة: English
• منشور في: 2022
• الموضوعات: Engineering::Computer science and engineering; Cross-Sectional Data; Predictive Computational Models
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/159990
• المؤسسة: Nanyang Technological University

Cross-sectional studies are widely prevalent since they are more feasible to conduct compared with longitudinal studies. However, cross-sectional data lack the temporal information required to study the evolution of the underlying dynamics. This temporal information is essential to develop predictiv...