Posteriors for parameters <i>θ</i> of the dimerization system for different weights in the ABC distance function. by Jonathan U. Harrison (5447603)

Data fitting and inference of the time-dependent parameters by TDINN algorithm for the local outbreaks in Xi’an, Guangzhou, and Yangzhou. by Mengqi He (5753525)

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Enhancement results of Nightstreet. by Hui Huang (4122)

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Fusion results of Nightstreet. by Hui Huang (4122)

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Detail separation layer results of Nato camp. by Hui Huang (4122)

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Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic by NELSON L. DIAS (8078003)

“…With these practical rules, simple summation algorithms provide sufficiently robust results for the calculation of the density function and its definite integrals. …”

Comparison of optimization performance of six ABC algorithms. by Shuhui Yu (1535500)

Datasheet1_Gait analysis comparison between manual marking, 2D pose estimation algorithms, and 3D marker-based system.pdf by Dimitrios Menychtas (16935831)

Effect of “nonfunctional group” on function. by Yuanchen Zhao (12905580)

“…(B) The coefficients of all species of a <i>S</i>–dimensional regression of function against all <i>S</i> species, for the same dataset as in (A). …”

Algorithm description and the effects of replay and forgetting on model performance. by Georgy Antonov (11938961)

“…(C) Left: without MB forgetting, the algorithm’s estimate of reward obtained for a given move corresponds to the true reward function. …”

Schematic view of the overall algorithm. by Betty Wutzl (6945248)

Posterior for parameter <i>θ</i> of the uniform toy model for different weights in the ABC distance function. by Jonathan U. Harrison (5447603)

“…Metrics to evaluate the performance of Algorithm 2 are shown in (b), (c), and (d) as <i>N</i> varies resulting in different total numbers of simulations from the model. …”

Posteriors for parameter <i>θ</i> in the simple diffusion model for different weights in the ABC distance function. by Jonathan U. Harrison (5447603)

Posterior for parameters <i>θ</i> of the bimodal toy model for different weights in the ABC distance function. by Jonathan U. Harrison (5447603)

“…<p>The posterior distribution for parameters <i>θ</i> = (<i>θ</i>₁, <i>θ</i>₂) of the bimodal toy model for different weights in the ABC distance function is shown in (a) and (b). ABC-SMC was used to provide estimates of the posterior, with <i>T</i> = 10 generations and <i>N</i> = 2, 000 particles at each generation with the posterior constructed from the closest 50% of the simulations (<i>α</i> = 0.5). …”

Similarity between the allegiance matrices of the multiplex SC-FC graph, the FC graph alone, and the SC graph alone, as a function of the topological scale for the group. by Arian Ashourvan (6685232)

Reconstruction performance across algorithms, dynamics, cell types, and recording length. by Christian Donner (3663007)

“…Dots depict the performance obtained on three different subnetworks of the same simulation. <b>E</b> Connectivity reconstruction performance (APS, MCC) as a function of recording time. …”

We recorded the distribution function of the one-step prediction time for CLPREM and its comparative models, as well as a curve graph showing the multiple of the comparative model’... by Xiaorui Wu (8322705)

Optimal model generation algorithm. by Anton Sobinov (9854047)

“…<b>C</b>. The optimization flow schematic showing the flow of calculations using the amalgamated algorithm of model generation with physical constraint. …”

Fig 4 - by Xutao Liu (13006965)

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Fig 9 - by Xutao Liu (13006965)

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