The structural equation modeling (SEM) has been widely used in the social and behavioral sciences. The SEM covers a wide variety of statistical models, including the factor analysis model and the regression model. An analyst develops an assumption of causal relationship and determines whether the as...
Graph neural networks have several valuable properties that make them uniquely suitable for modeling atomic systems: invariance to permutations, rotations, and translation; natural encoding of the locality of interactions. In the recent Open Catalyst benchmark5, GNNs solidly outperform the physics-based ...
[5] D. Cao, X. He, L. Nie, X. Wei, X. Hu, S. Wu, and T.-S. Chua. Cross-platform app recommendation by jointly modeling ratings and texts. ACM TOIS, 2017. [6] J. Chen, B. Sun, H. Li, H. Lu, and X.-S. Hua. Deep ctr prediction in display advertising. In MM, 201...
We used a Bayesian sparse modeling approach to select among 80 metrics of climate and applied the approach to 19 datasets of bird, insect, and plant population responses to abiotic conditions as case studies of how the method can be applied for climate variable selection in a time se...
Promoting sparsity among epistatic interactions is a powerful inductive bias for predictive modeling because it reduces the problem dimension without biasing the model towards a subset of (low-order) interactions. Despite its benefits, promoting sparsity among epistatic interactions has not been studied ...
(GPR43) as possible alternative methods. We include the conceptually most simple gradientless descent as reference method to assess the benefit of more intricate approaches. All our ML methods produce reasonable parameter sets as exemplified by the small errors (δϵ) in Table1. Comparing also ...
The autonomous distillation of physical laws only from data is of great interest in many scientific fields. Data-driven modeling frameworks that adopt spar... A Purnomo,M Hayashibe - 《Scientific Reports》 被引量: 0发表: 2023年 Data-driven sparse identification of nonlinear dynamical systems using...
Efficient inverse method for structural identification considering modeling and response uncertainties. Chinese Journal of Mechanical Engineering, 2022, 35: 75. Article Google Scholar H Inoue, J J Harrigan, S R Reid. Review of inverse analysis for indirect measurement of impact force. Applied ...
Teng Z, Arthur S, Yi W, Gilad L (2010) Hybrid linear modeling via local best-fit flats. Int J Comput Vis 100(3):217–240 MathSciNet MATH Google Scholar Zhuang L, Gao H, Lin Z, Ma Y, Zhang X, Yu N (2012) Non-negative low rank and sparse graph for semi-supervised learning....
Efficient inverse method for structural identification considering modeling and response uncertainties. Chinese Journal of Mechanical Engineering, 2022, 35: 75. Article Google Scholar H Inoue, J J Harrigan, S R Reid. Review of inverse analysis for indirect measurement of impact force. Applied ...