Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling by Giacomo Janson (8138517)

“…<div><p>The most frequently used approach for protein structure prediction is currently homology modeling. …”

Reconstructing <i>sparse</i>, binary patterns using message passing algorithms and PCA. by Sebastian Goldt (14522594)

“…Lines depict the result of the state evolution, while crosses denote the performance of the AMP algorithm on an instance of the problem. While AMP performs the same starting from both initialisations for <i>ρ</i> = 0.1 and <i>ρ</i> = 0.3, there is a gap in performance for <i>ρ</i> = 0.05, which might hint at the existence of a hard phase (see main text). …”

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

Top-ranked hub genes identified by 5 cytoHubba algorithms. by Jun Li (6494)

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

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Results on solving TSS using (1 + 1)-WEA_v3 with different values of <i>Q.</i> by Alexander Andreev (16822333)

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Output groupings of the 3 algorithms for a linear degradation chain of <i>N</i> = 3 metabolites. by Yuanchen Zhao (12905580)

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Illustration of the DLNN used in this study, including 10 inputs, three hidden layers, and one output variable. by Tuan Anh Pham (1346049)

Verification of the in-line PS function. by Raul Castañeda (13932971)

Algorithm and simulation parameters. by Derek E. Moulton (7053563)

“…The approach is as follows: we use a Quality-Diversity algorithm, a type of black-box optimization algorithm, to explore the range of concentration profiles emerging as solutions of a molecular model, and that define growth patterns for the mechanical model. …”

Average classification accuracies for fft and stack methods, LSTM, Bi-LSTM, and CNN algorithms. by Jamila Akhter (21144252)

Table_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.DOCX by Shakiru A. Alaka (9302864)

“…Regression and machine learning models, including random forest (RF), classification and regression tree (CART), C5.0 decision tree (DT), support vector machine (SVM), adaptive boost machine (ABM), least absolute shrinkage and selection operator (LASSO) logistic regression, and logistic regression models were used to train and predict the 90-day functional impairment risk, which is measured by the modified Rankin scale (mRS) score > 2. …”

Genetic Algorithm parameter search. by Elishai Ezra-Tsur (11888717)

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(a-b) The LASSO algorithm was used for hyperparameter tuning and identification of the important predictive features. by Devi Soorya Narayana Sasikumar (22331743)

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Genetic Algorithm for Automated Parameterization of Network Hamiltonian Models of Amyloid Fibril Formation by Gianmarc Grazioli (6752297)

Subjects: “…randomly parametrized models…”

Features selected by optimization algorithms. by Afnan M. Alhassan (18349378)

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Continuous Probability Distributions generated by the PIPE Algorithm by LUIS G.B. PINHO (14073372)

“…<div><p>Abstract We investigate the use of the Probabilistic Incremental Programming Evolution (PIPE) algorithm as a tool to construct continuous cumulative distribution functions to model given data sets. …”

<i>I</i>-<i>U</i> characteristics using all investigated methods in Table 1: RTC-F solar cell. by Ziad M. Ali (12516532)

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Two-stage object detection algorithm process. by Xutao Liu (13006965)

“…<div><p>Since various dance teaching systems have attracted much attention with the development of Artificial Intelligence (AI) technology, this paper improves the recognition performance of Latin dance teaching systems by optimizing the action recognition model. Firstly, the object detection and action recognition technology under the current AI technology is analyzed, and the Two-stage object detection algorithm and One-stage object detection algorithm are evaluated. …”

<i>I</i>-<i>U</i> characteristics using all investigated methods in Table 3: MSX-60 module. by Ziad M. Ali (12516532)

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