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)

“…<p dir="ltr"># m:n-CAk Wildfire Simulation Project</p><p dir="ltr"><br></p><p dir="ltr">## Overview</p><p dir="ltr">This project simulates the spread of a wildfire using a cellular automaton model based on m:n-CAk. The simulation takes into account various factors such as vegetation type, and humidity levels, to model the propagation of the fire over a landscape. …”

Python code for hierarchical cluster analysis of detected R-strategies from rule-based NLP on 500 circular economy definitions by Zahir Barahmand (18008947)

“…</p><p dir="ltr">This Python code was optimized and debugged using ChatGPT-4o to ensure implementation efficiency, accuracy, and clarity.…”

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

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. …”

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)

Results obtained from the Bistable Gut Inflammation Detector model. by Fabricio Cravo (21387854)

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Python sript. by Kan Jia (6438599)

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

(a) System dynamics: schematic representation of all the reactions in the Tree model, which are aging, reproduction, color cycle, and competition. by Fabricio Cravo (21387854)

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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)

Left schematic of the XOR gate implementation [11]. by Fabricio Cravo (21387854)

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Simulated dynamics of the Mutual Annihilation protocol [26]. by Fabricio Cravo (21387854)

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Heatmap showing the simulated output of the XOR circuit by Tamsir <i>et al</i>. [11]. by Fabricio Cravo (21387854)

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Simulation results for the phage communication circuit from Pathania <i>et al</i>. [5]. by Fabricio Cravo (21387854)

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Matching products with reactants for the example meta-reaction where S1 and S2 are distinct meta-species. by Fabricio Cravo (21387854)

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