Computational intelligence and neuroscience
36097558
Cracks are one of the most common types of imperfections that can be found in concrete pavement, and they have a significant influence on the structural strength. The purpose of this study is to investigate the performance differences of various spat...
The development of computational modeling and simulation have immensely benefited the study of cardiac disease mechanisms and facilitated the optimal disease diagnosis and treatment design. The dynamic propagation of cardiac electrical signals are of...
Many authors have been working on approaches that can be applied to social robots to allow a more realistic/comfortable relationship between humans and robots in the same space. This paper proposes a new navigation strategy for social environments by...
Medical decision making : an international journal of the Society for Medical Decision Making
35735216
PURPOSE: Metamodels are simplified approximations of more complex models that can be used as surrogates for the original models. Challenges in using metamodels for policy analysis arise when there are multiple correlated outputs of interest. We devel...
Mathematical biosciences and engineering : MBE
36032012
With the unprecedented development of big data, it is becoming hard to get the valuable information hence, the recommendation system is becoming more and more popular. When the limited Boltzmann machine is used for collaborative filtering, only the s...
Neural networks : the official journal of the International Neural Network Society
35944369
Learning continually from sequentially arriving data has been a long standing challenge in machine learning. An emergent body of deep learning literature suggests various solutions, through introduction of significant simplifications to the problem s...
Journal of chemical theory and computation
35858242
We introduce an unsupervised clustering algorithm to improve training efficiency and accuracy in predicting energies using molecular-orbital-based machine learning (MOB-ML). This work determines clusters via the Gaussian mixture model (GMM) in an ent...
The application of machine learning to the materials domain has traditionally struggled with two major challenges: a lack of large, curated data sets and the need to understand the physics behind the machine-learning prediction. The former problem is...
This study extends the accurate and transferable molecular-orbital-based machine learning (MOB-ML) approach to modeling the contribution of electron correlation to dipole moments at the cost of Hartree-Fock computations. A MOB pairwise decomposition ...
IEEE journal of biomedical and health informatics
35939478
In this paper, we propose a prior guided transformer for accurate radiology reports generation. In the encoder part, a radiograph is firstly represented by a set of patch features, which is obtained through a convolutional neural network and a tradit...