Comparison of performance between our next reaction implementation and the Python library from Ref. [3]. by Samuel Cure (22250922)

“…<p>We simulate SIR epidemic processes on Watts-Strogatz networks with parameters <i>k</i>₀ = 5, <i>p</i> = 0.1 <b>(a)</b> and Barabási-Albert networks with parameter <i>m</i> = 5 <b>(b)</b> using the Python wrapper of our C++ implementation and compare its performance with the Python library from Ref. …”

Python implementation of a wildfire propagation example using m:n-CAk over Z and R. by Pau Fonseca i Casas (9507338)

A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me... by Hector Torres (11708207)

“…<p><b>(a)</b> UMAP, t-SNE, PCA, and Diffmap were first generated using the Python libraries Scikit-learn, UMAP, and PyDiffmap within Jupyter to generate static graphs as a starting point. …”

SCADET algorithm parameter configuration (Python implementation). by Xiaolong Zhang (470454)

Example change statistic implementations. by Alex Stivala (8356257)

“…ALAAMEE implements both the stochastic approximation and equilibrium expectation (EE) algorithms for ALAAM parameter estimation, including estimation from snowball sampled network data. …”

PYTHON by Kan Jia (21666161)

Reproducible implementation for article: Reproducibility study of the modular and reusable model of epithelial transport in the proximal convoluted tubule by Leyla Noroozbabaee (14301173)

Python sript. by Kan Jia (6438599)

In silico Toxicity Prediction, PA represent the Prediction accuracy, and AS represents the average similarity, toxicity profile (). by Kassim Folorunsho Adebambo (22806479)

Overview of the implemented simulation tool and training framework in Diffrax. by Paul van Lent (16876977)

Cost functions implemented in Neuroptimus. by Máté Mohácsi (20469514)

“…However, using most of these software tools and choosing the most appropriate algorithm for a given optimization task require substantial technical expertise, which prevents the majority of researchers from using these methods effectively. To address these issues, we developed a generic platform (called Neuroptimus) that allows users to set up neural parameter optimization tasks via a graphical interface, and to solve these tasks using a wide selection of state-of-the-art parameter search methods implemented by five different Python packages. …”

Representative examples of scanned intake forms. by Yojiro Umezaki (5916593)

Secure Python Code Manager: A Tool for Protected Python Code Distribution and Management by Pavel Izosimov (20096259)

“…This tool allows developers worldwide to <b>share Python code securely</b>, ensuring their intellectual property is better protected from unauthorized access and misuse.…”

Parameter estimates and estimated standard errors from the EE algorithm. by Alex Stivala (8356257)

Python file of the computational framework. by Benoit Haut (9753029)

Segmentation module training details. by Khelina Fedorchuk (19130089)

Type II error rate from estimation of simulated outcomes using the EE algorithm. by Alex Stivala (8356257)

Type I error rate from estimation of simulated outcomes using the EE algorithm. by Alex Stivala (8356257)

A Representative example of organ surface data before and after editing. by Takashi Kimura (178058)

Apple point cloud generated by python script. by Xiaoyang Liu (1815211)