Discriminant function analysis results represented in multivariate space. by Thiago Orion Simões Amorim (6808244)

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Example of the CNF function for off-axis DHM holograms recorded in a non-telecentric configuration. by Raul Castañeda (13932971)

Data_Sheet_1_Decoding emotional resilience in aging: unveiling the interplay between daily functioning and emotional health.PDF by Minhua Guo (18392646)

Iteration versus fitness function. by B. Venkatesh (17202747)

Visualizing the scatter plot of the drought (red) versus no-drought (green) and the support vectors (black) using the SVM section 4 classification algorithm. by J. Emmanuel Johnson (9579567)

A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density. by Hassan Mehboob (8960273)

“…<p>A detailed process of iterative simulation coupled with bone density algorithm; (a) a function of stimulus and related bone density changes, and (b) iterative calculations of finite element analysis coupled with user’s subroutine for changes in bone density.…”

Loss functions used in the synthetic data analysis to assess the numerical accuracy of the B-net and D-net estimates. by Jarod Smith (11999040)

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

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

Subjects:

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

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Geometric interpretation and data visualisation equivalent describing the DI algorithmic pipeline. by Borjan Milinkovic (21349908)

Signal detection algorithm adapted from [1] yields exponential distributions and unrealistic mean durations of percepts. by Quynh-Anh Nguyen (847240)

“…(Bottom) Trial-by-trial applications of the signal detection algorithm from [<a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1008152#pcbi.1008152.ref001" target="_blank">1</a>] with A: <i>C</i>_<i>th</i> = 4.01 and B: <i>C</i>_<i>th</i> = 4.21 yield exponentially distributed subsequent percept durations for <i>I</i> (blue) and <i>S</i> (red). …”

A) Ranking of models trained on different feature sets across all tested algorithms, sorted by their F1-score. by Jose Cleydson F. Silva (8685594)

Parameter search fine-tuned through Differential Evolution algorithm. by Bolaji P. Eniwaye (12915339)

Subjects: “…differential evolution algorithm…”

Multiresolution Spectro-Temporal Sound Analysis (MRSTSA) algorithm. by Dario Dematties (6812390)

<b>Fig. 3 | Performance analysis of microrobot navigation in various environments using reinforcement learning algorithms.</b> by Mahmoud Medany (20766911)

“…<b>e.</b> Impact of different reward functions on the rate of target achievement. …”

The training process for PV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

The training process for AV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

The training process for TV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

The training process for MV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)