Procedure of the DCT-based EIT algorithm. by Rongqing Chen (249906)

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Parameters used to train the xgboost final models through the extreme gradient boosting algorithm in this work (n = 11,009 species). by Luis Javier Madrigal-Roca (17743035)

If datasets are small and/or noisy, linear-regression-based algorithms for identifying functional groups outperform more complex versions. by Yuanchen Zhao (12905580)

“…Both versions are evaluated on the same synthetic datasets with a 3-group ground truth. Each algorithm return a set of coarsened <i>variables</i> (a grouping of species into three groups) and a <i>model</i> that uses these variables to predict the function. …”

The main steps of the general algorithm. by Dror Mughaz (18017583)

The number of inactive nodes as a function of time steps in (a) a random network and (b) a scale-free network. by Waseem Al-Aqqad (14123917)

Policy network (<i>θ</i>′) of SAM to accommodate PPO algorithm. by Zhenhan Huang (12107002)

Automatic cropping algorithm. by Thomas W Georgi (12427189)

Steps in the proposed Apriori algorithm. by Yongkang Ding (21807539)

Step-function plots of longitudinal dose changes for esmolol separated by cluster assignment analyzed using 2, 3, and 4 clusters. by Mary-Carty Pittman (21161824)

Step-function plots of longitudinal dose changes for propranolol separated by cluster assignment analyzed using 2, 3, and 4 clusters. by Mary-Carty Pittman (21161824)

Step-function plots of longitudinal dose changes for captopril separated by cluster assignment analyzed using 2, 3, and 4 clusters. by Mary-Carty Pittman (21161824)

ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space by Koushik Naskar (7510592)

“…For the numerical case, user can directly provide <i>ab initio</i> data (adiabatic PESs and NACTs) as input files to this software or can generate those input files through in-built python codes interfacing MOLPRO followed by ADT calculation. …”

Training accuracy/loss as a function of epochs for different datasets. by Hiam Alquran (17636906)

Overview of the Cell2Spatial algorithm. by Huamei Li (8815955)

Show parameter <i>N</i>_<i>x</i> for different topologies. by Maryam Shadi (14237349)

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Flowchart of the specific incarnation of the BO algorithm used in the experiments. by Lisa Laux (9367681)

“…To choose the next pipeline configuration to evaluate, the BO algorithm uses an Expected Improvement function to trade off maximisation of QS with the need to fully learn the GP. …”

Flowchart of step() function. by Raed Alharthi (18340157)

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)

Schematic showcasing main steps involved in the generation of a new daughter node <i>C</i>_<i>i</i> and subsequently a new branch <i>B</i>_<i>i</i>. by Diana C. de Oliveira (9220729)

Simulation Results Plot of the SBW System Response: (a) Step response curve of the SBW system; (b) Sine response curve of the SBW system; (c) Steady state error curve of the SBW sy... by Honglei Pang (22693724)

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