Python sript. by Kan Jia (6438599)

Overview of the SBML models used in this study. The collection of models was retrieved from Biomodels [43] and a previously reported collection of SBML benchmark models [11]. The n... by Paul van Lent (16876977)

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Jaxkineticmodel allows for hybridizing kinetic models with neural networks. by Paul van Lent (16876977)

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Analysis of convergence properties for a collection of SBML models. by Paul van Lent (16876977)

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Fitting a feast/famine cycle to a glycolysis model. by Paul van Lent (16876977)

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Five Operator Lattice Simulation by James McDaniel (22522571)

“…<p dir="ltr">This dataset contains the Python simulation code and supporting documentation for the paper <i>A Five-Operator Lattice of Consciousness: A Logical Framework for Mediation Between Implicit and Explicit Processing</i> (McDaniel, 2025).…”

ALAAM models for the Deezer networks, with liking “alternative” music as the outcome variable. by Alex Stivala (8356257)

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

Models estimated using ALAAMEE for the Deezer networks, with liking jazz as the outcome variable. by Alex Stivala (8356257)

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Exploring the integration of metaverse technologies in engineering education through the SAMR model by Snezhana Dineva (22444471)

“…The final deliverable is a plan for phased integration of metaverse learning into a Python programming course following this model, building on existing best practices.…”

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

Supporting data for "Interpreting complex ecological patterns and processes across differentscales using Artificial Intelligence" by Yifei Gu (9507104)

“…The detailed implementation, source code and demo dataset are included in dedicated folders for each chapter.…”

ZILLNB_Model by Qinhuan Luo (21288548)

“…<p dir="ltr">Acquire latent variables using deep-learning based model implemented in python</p>…”

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

“…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. Neuroptimus also offers several features to support more advanced usage, including the ability to run most algorithms in parallel, which allows it to take advantage of high-performance computing architectures. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…We believe that BaNDyT is the first software package to include specialized and advanced features for analyzing MD simulation trajectories using a probabilistic graphical network model. We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…We believe that BaNDyT is the first software package to include specialized and advanced features for analyzing MD simulation trajectories using a probabilistic graphical network model. We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”

BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

“…We believe that BaNDyT is the first software package to include specialized and advanced features for analyzing MD simulation trajectories using a probabilistic graphical network model. We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”

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)

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code implementing the finite element method and finite difference method from Hybrid PDE-ODE Models for Efficient Simulation of Infection Spread in Epidemiology by Kristina Maier (20520371)

“…This dataset contains code implementing the finite element method based on Kaskade 7 (C++) and code implementing the finite difference method (Python) for the development of hybrid PDE-ODE models aimed at efficiently simulating infection spread in epidemiology. …”

Numerical data and codes for "Noisy Probabilistic Error Cancellation and Generalized Physical Implementability" by Tian-Ren Jin (18781930)

“…We numerically simulate the bias of noisy probabilistic error cancellation with noisy Pauli operations and the bias of error model violation.</p><p dir="ltr">Codes are written in Python, which is contained in the folder "code". …”