Demonstration of the combinatorial Hill functions (A and B), and the regulation function (C and D) under the regulation of an activator and a repressor. حسب Ruihao Li (2908991)

Pipeline of the interactor algorithm. حسب Jose Cleydson F. Silva (8685594)

Comparison of overall (a) Accuracy and (b) Label request results between ROAL and AOL. حسب Honglan Huang (341951)

Evolutionary processes on special functions (a) NMO-SARA vs MS-GEP-A (b) GEP vs MS-GEP-I (c) FF-GEP vs MS-GEP. حسب Jin Ding (11522)

CPU usage of benchmark function: (a) CPU Usage during the Execution of Benchmark Functions F21-F30, (b) CPU Usage during the Execution of Benchmark Functions F31-F40 and (c) CPU Us... حسب Ruyi Dong (9038174)

Iteration curve of benchmark function: (a) Convergence curves of the average best fitness for functions F21-F30, (b) Convergence curves of the average best fitness for functions F3... حسب Ruyi Dong (9038174)

Comparative performance evaluation of 3Mont with other feature selection algorithms over 10 iterations. حسب Miray Unlu Yazici (14792680)

الموضوعات:

Population diversity comparison on all function (a) NMO-SARA vs MS-GEP-A (b) GEP vs MS-GEP-I (c) FF-GEP vs MS-GEP. حسب Jin Ding (11522)

Example of use of the slightly off-axis strategies. حسب Raul Castañeda (13932971)

Example of the fully-compensated phase reconstruction package for off-axis DHM holograms recorded in telecentric configuration. حسب Raul Castañeda (13932971)

Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large. حسب Panfei Li (22379086)

"…<p>Objective function values of the algorithms across individual problem instances grouped by scale: (a) Small, (b) Medium, (c) Large, (d) Super-Large.…"

The SSIM for the different algorithms. حسب Bingbing Li (461702)

"…Unlike traditional threshold functions, the improved threshold function is a continuous function that can avoid the pseudo Gibbs effect after image denoising and improve image quality. …"

The number of core promoter elements and TF binding sites predicted for four promoters with YAPP, GPMiner and ElemeNT algorithms. حسب Ali Hosseini Rad S. M. (9167497)

Skeletonisation algorithm. حسب Jordan Hembrow (16908051)

BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data حسب Jean-Christophe Lachance (6619307)

"…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …"

Scores of municipalities projected on the first and second functional PC (A), and first and third functional PC (B). حسب Manuel Ribeiro (17889313)

Flowchart of the general algorithm for one trial. حسب Junying Wang (509009)

Computational and resource efficiency of different algorithms. حسب Rui Li (4631)

Functional validation of the metastasis-predictive genes inferred by PLUS from TCGA data. حسب Junyi Zhou (495644)

Search for Correlations Between the Results of the Density Functional Theory and Hartree–Fock Calculations Using Neural Networks and Classical Machine Learning Algorithms حسب Saadiallakh Normatov (20682324)