Recently, diffusion models have been proven to perform remarkably well in text-to-image synthesis tasks in a number of studies, immediately presenting new
These methods often involve complex mathematical models and algorithms to simulate degradation. Motivated by the success of deep learning in a wide range of fields, a large number of data-driven methods22,23,24,25,26,27,28,29,30,31,32,33 based on deep learning have been proposed. These ...
data-driven algorithms. Most of these approaches have, however, been restricted to linear material properties such as the effective elastic stiffness in three dimensions7,8or Poisson’s ratio9. Extensions to nonlinearity (for example, via multi-material configurations) have been presented recently10but...
The proposed hybrid L-systems–DLA schemes could be further used to this end, improving different algorithms, or devices, such as, for instance, robots swarms. For example, in Evolutionary Computation algorithms, a direct extension of the proposed system could be employed, by defining the ...
are shown in Figs.2E and F, respectively. Although the binding pose accuracy decreased as the ligand size increased, our models performed better for larger ligands than the baseline methods (Fig.2E), indicating their ability to efficiently handle many degrees of freedom. Besides, our models were...
Pattern formation in evolutionary dynamics has been studied as an example of phenomena inherent to many natural systems. It is well known that the reaction–diffusion models are used to study self-organization phenomena in physical, chemical and biological systems (see, for example, Refs. [1], ...
- evolutionary graph theory - epidemic models on graphs - data-driven approaches - temporal networks - seeding strategies - optimization of dynamic processes in networks === IMPORTANT DATES === Submission deadline: 9 August 2015 First round decision: end of November 2015 ...
in application areas ranging from engineering to finance. On the other hand, PINN models have also been extended to backward problems, such as advection-dispersion equations55, stochastic problems56, flow problems57, and conservation laws58. In these backward problems, the training data are inputted...
Based on the evolutionary algorithms of the four complex networks, the evolution of knowledge network is regarded as that of complex networks. With the heterogeneity of knowledge level, knowledge...doi:10.1007/s10586-018-2559-3Zhang, LiWei, Qifeng...
(Xie et al.,1997). A common challenge with these methods is the need for a closed-form representation of the diffusion process to use in parameter estimation algorithms. Actual sales data are compared against forecasted sales, with optimization used to minimize forecasting errors. We use our ...