The run time for each algorithm in seconds. by Edward Antonian (21453161)

“…The goal of this paper is to examine several extensions to KGR/GPoG, with the aim of generalising them a wider variety of data scenarios. The first extension we consider is the case of graph signals that have only been partially recorded, meaning a subset of their elements is missing at observation time. …”

Temporal response patterns determined by Dirichlet Process-based clustering algorithm across amplitudes and stimuli. by Dinh K. Tang (20469082)

The actual training effect of four algorithms on original photo data (All images are original images taken by the author). by Xiaojun Wang (50332)

Subjects:

Completion times for different algorithms. by Jianbin Zheng (587000)

“…The algorithm employs recurrent neural networks to capture and process historical information. …”

Algorithm process. by Wei Cui (92129)

GA pseudo-code. by Jianpeng Zhang (528185)

Subjects:

Improve algorithm process. by Ziwei Wu (11386352)

Dataset for Fine-Tuning Code Generation Models: Kannada-English Algorithmic Statements and Python Code by Goutami Sooda (20714729)

Impact of multiunit merging on neural information encoding. by Daniel Suárez-Barrera (22676654)

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Running time in the PPO process. by Yunhu Huang (21402795)

DARTS algorithm process. by Yuxuan Ji (13991895)

Algorithm optimization process. by Zhihao Li (359073)

Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

Etalon2 observations and algorithmic processing results. by Jinyu Wang (381467)

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Lares2 observations and algorithmic processing results. by Jinyu Wang (381467)

Subjects:

Etalon1 observations and algorithmic processing results. by Jinyu Wang (381467)

Subjects:

Processing time of each processing task. by Heshuai Shen (21696119)

Time complexity of different safety algorithms. by Most. Fatematuz Zohora (19429152)

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Pseudo-code for the study design model. by Jianpeng Zhang (528185)

Subjects:

The segmentation process of this new algorithm. by Niu Meng (22032810)

“…The experimental results show that the proposed method shortens the execution time by nearly 40% compared with the self-organized mapping network, and the average color difference (ΔE) of each region after color segmentation is as low as 0.7, which is significantly better than other algorithms. …”