The preferential attachment model of Barabasi and Albert network has been used to explain the download network.韩定定刘锦高马余刚蔡翔舟沈文庆中国物理快报(英文版)Han D-D,Liu J-G,Ma Y-G,Cai X-Z,and Shen W-Q.Scale-free download network for publication.Chinese Physics Letter. 2004Ding-Ding H, ...
We show that our generative model always yields a power-law scaling in P(k), recovering the ubiquitously observed scale-free property42,43, and, at the same time, it allows full control over P(kℓ), i.e., bounded or scale-free with any desired scaling exponent. Indeed, P(kℓ) ...
Is the network scale-free? What else can you discover? 5.7 Explanatory models Figure 5.2: The logical structure of an explanatory model. We started the discussion of networks with Milgram’s Small World Experiment, which shows that path lengths in social networks are surprisingly small; hence, ...
Most importantly, our CNN-based generative model identifies disordered structures with scale invariance following the power law. The heavy-tailed distributions in these scale-free structures lead to an increase of two to four orders of magnitude in robustness to unexpected structural errors when ...
Scale-free network structure accounted for IRIs between particular animal names in terms of minimal path lengths, as well as IRI distributions in terms of heavy-tailed functions. Observed and model distributions were highly similar to each other, and very similar to inverse powe...
In a large-scale model, the parameters, their gradients, and the L-BFGS historical vectors are too large to fit in the memory of one single computational machine. This also makes the computations too complex to be handled by the processor. Due to this, there is a need for distributed comp...
This approach does not explicitly carry out fits of the model to the data; instead, it assumes that a “good” fit to the data has already been achieved, and it then provides an estimate of the uncertainty in each of the fitted parameters via a second-order expansion of the logarithmic ...
An active 3D reconstruction method scans a target through a 3D scanning device, followed by calculating the depth information of the object and obtaining point cloud data, which are used to restore the 3D model of the target. The main steps are data registration, point cloud data pre-...
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Tune the timeouts of operations of SAPHana and SAPHanaTopology. Start with the parameter values PREFER_SITE_TAKEOVER=”true”, AUTOMATED_REGISTER=”false” and DUPLICATE_PRIMARY_TIMEOUT=”7200”. Always wait for pending cluster actions to finish before doing something. Set up a test cluster for...