Confusion matrices depict the performance of various ML algorithms. by Caroline L. Alves (14271413)

Power flow and cost optimization with APSO variant-16 of APSO algorithm (b). by Muhammad Ahmad Iqbal (11851338)

Uncovering hierarchical community structure in a synthetic graph. by Arian Ashourvan (6685232)

“…First, we use the more traditional approach of maximizing a single-layer modularity quality function [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0215520#pone.0215520.ref053" target="_blank">53</a>] with the Newman-Girvan null model [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0215520#pone.0215520.ref057" target="_blank">57</a>] using a Louvain-like locally greedy algorithm [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0215520#pone.0215520.ref054" target="_blank">54</a>]. …”

(a) Flow chart for PSO algorithm (b) position and velocity update of particles (c) convergence of PSO. by Waqas Anjum (8415186)

Constructing the dynamical law. by Robert Marsland (8616483)

Definitions of global parameters used for constructing random ecosystems. by Robert Marsland (8616483)

Average quality scores of the models of the analysis set as a function of the <i>w</i>_<i>SP</i> with which the DOPE potential has been included in the objective function... by Giacomo Janson (8138517)

Acurracy comparison of CCA and FBCCA algorithms. by Hossein Hamidi Shishavan (19688384)

Reward function related parameters. by Honglei Pang (22693724)

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Dataset of networks used in assessing the Troika algorithm for clique partitioning and community detection by Samin Aref (4683934)

“…</p><p dir="ltr"><br></p><p dir="ltr">For more information about the data, one may refer to the article below:</p><p dir="ltr">Aref S, Ng B (2025) Troika algorithm: Approximate optimization for accurate clique partitioning and clustering of weighted networks. …”

Convergence curves of different algorithms on the benchmark functions. by Aihua Guo (13267712)

Algorithm results based on experimental likelihood functions. by Nicolas Herzig (9230425)

PS-VAE hyperparameter selection for the head-fixed mouse dataset. by Matthew R. Whiteway (11467528)

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The PS-VAE successfully partitions the latent representation of a head-fixed mouse video [46]. by Matthew R. Whiteway (11467528)

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The multi-session PS-VAE (MSPS-VAE) accounts for session-level differences between videos in the head-fixed mouse dataset [46]. by Matthew R. Whiteway (11467528)

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The PS-VAE enables targeted downstream behavioral analyses of the two-view mouse video. by Matthew R. Whiteway (11467528)

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The PS-VAE enables targeted downstream behavioral analyses of the mouse face video. by Matthew R. Whiteway (11467528)

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Neural decoding video still. by Matthew R. Whiteway (11467528)

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The PS-VAE enables targeted downstream neural analyses of the mouse face video. by Matthew R. Whiteway (11467528)

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The PS-VAE successfully partitions the latent representation of a freely moving mouse video. by Matthew R. Whiteway (11467528)

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