Comprehensive Re, F1 and Pre values of FcaNet-CycleGAN model. by Xiaojun Wang (50332)

Subjects:

A flow diagram to explain the algorithm named 2BDP (Biomarker Discovery Process at Binomial Decision Point) that we used to find the best fitting model to predict RRiF. by Nabarun Chakraborty (535772)

<b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

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Average CPU time (s) of all the referenced algorithm on benchmark function. by Aihua Guo (13267712)

“…<p>Average CPU time (s) of all the referenced algorithm on benchmark function.…”

Spike sorting performance dependence on pre-recording duration. by Tjitse van der Molen (20391106)

Scheduling time of five algorithms. by Huichao Guo (14515171)

“…<div><p>This paper aims to solve the scheduling optimization problem in the emergency management of long-distance natural gas pipelines, with the goal of minimizing the total scheduling time. To this end, the objective function of the minimum total scheduling time is established, and the relevant constraints are set. …”

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

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

Workflow of our study to evaluate the performance of GNNs compared to benchmark algorithms. by Daniel Walke (21680915)

Comparison of the running time(in ms) of the three algorithms. by Yaling Zhang (1687540)

Run times of two algorithms. by Gourab Saha (8987405)

“…Furthermore, crop yield is predicted using Linear Regression and Random Forest, achieving accuracies of 93.49% and 95.87%, respectively, while using RMSE (Root Mean Squared Error) as the loss function. The LSTM model is used for healthy vegetation area forecasting highlighting the changes of the vegetation area over time. …”

Design and implementation of DelaySSA. The input data for DelaySSA are reaction information, initial states, parameters and delays. Combining these into the simulation function, th... by Ziyan Jin (21021976)

Comparison of algorithms in two cases. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

Flow of the NSGA-II algorithm. by Yi Tao (178829)

Subjects: “…evolutionary genetic algorithm…”

A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data by Anthony S. Barente (14035175)

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PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

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An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

Comparison of running times. by Dong-Jun Lee (14068673)

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Average running times for the different algorithms. by Ayush Dogra (17054597)

Computational time of each algorithm—Part I. by Xuan Chen (158617)