Data_Sheet_1_Brian2CUDA: Flexible and Efficient Simulation of Spiking Neural Network Models on GPUs.pdf by Denis Alevi (11805765)

“…These advances, however, are often not available to researchers interested in simulating spiking neural networks, but lacking the technical knowledge to write the necessary low-level code. Writing low-level code is not necessary when using the popular Brian simulator, which provides a framework to generate efficient CPU code from high-level model definitions in Python. …”

SecurityGuidelinesRetrievalForPythonCodeGen by Catherine Tony (18368913)

“…Using Task-Specific Guidelines for Secure Python Code Generation: Replication Package"</p><p dir="ltr">This replication package contains SecGuide along with the results of each step followed in its creation, the scripts that implement all the prompting approaches and the code generated by the LLMs using these approaches. …”

Replacing the final prediction layer of end-to-end trained Transformer Networks with gradient boosting models improves performance. by Alexander Kroll (9304225)

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Python implementation of the geometric minimum action method (gMAM) by Pascal Wang (10130612)

“…<p>The Python 3 script <code>gmam_demo.py</code> found in this repository implements the geometric minimum action method (gMAM) as presented in Heymann, M. and Vanden-Eijnden, E. (2008), "The geometric minimum action method: A least action principleon the space of curves." …”

Comparative analysis of WordNet replacement impact on data distribution. by Enock Niyonkuru (21246879)

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ProSmith outperforms the ESP model in the prediction of enzyme-substrate pairs especially for molecules with limited representation in the test data. by Alexander Kroll (9304225)

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Performance metrics for all three trained gradient boosting models with different input vectors and for their combined weighted mean prediction. by Alexander Kroll (9304225)

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Runtime comparison using our API vs published/standard Python implementations. by Lu Bin Liu (14279482)

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Collision Efficiency Parameter Influence on Pressure-Dependent Rate Constant Calculations Using the SS-QRRK Theory by E. Grajales-González (6083633)

“…To overcome this underestimation problem, we evaluated and implemented in a bespoke Python code two alternative definitions for the collision efficiency using the SS-QRRK theory and tested their performance by comparing the pressure-dependent rate constants with the Rice–Ramsperger–Kassel–Marcus/Master Equation (RRKM/ME) results. …”

Collision Efficiency Parameter Influence on Pressure-Dependent Rate Constant Calculations Using the SS-QRRK Theory by E. Grajales-González (6083633)

“…To overcome this underestimation problem, we evaluated and implemented in a bespoke Python code two alternative definitions for the collision efficiency using the SS-QRRK theory and tested their performance by comparing the pressure-dependent rate constants with the Rice–Ramsperger–Kassel–Marcus/Master Equation (RRKM/ME) results. …”

The optimal ProSmith models combine predictions based on the multimodal Transformer Network with predictions based on separate numerical representations of proteins and small molec... by Alexander Kroll (9304225)

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ProSmith outperforms previous models in the prediction of Michaelis constants <i>K</i>_M especially for enzymes not highly similar to proteins in the training set. by Alexander Kroll (9304225)

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Data_Sheet_1_An Open-Source Tool for Anisotropic Radiation Therapy Planning in Neuro-oncology Using DW-MRI Tractography.pdf by Kesshi Jordan (7329089)

“…We present an open-source WMPL tool, implemented in the package Diffusion Imaging in Python (DIPY), and code to convert the resulting WMPL map to anisotropic contours for RT in a commercial treatment planning system. …”

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

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Python code for ray-tracing through Cartesian surfaces by Alberto Silva (8373543)

Schematic example of multiscale modelling implementation. by Robyn M. Stuart (3754000)

Low- and high-level subspace noise for the reverse-correlation of visual and audio stimuli. by Juan José Burred (6555578)

Local Python Code Protector Script: A Tool for Source Code Protection and Secure Code Sharing by Pavel Izosimov (20096259)

“…</p><h2>Key Features</h2><ul><li><a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>Code Obfuscation in Python</b></a>: Implements multi-level protection with dynamic encryption and obfuscation techniques, making it an effective <a href="https://xn--mxac.net/secure-python-code-manager.html" target="_blank"><b>Python obfuscator</b></a>.…”

A Cell-Based, Dynamic Flow Direction Model (DFD Model) for Water Balance Calculations Simulating Overland Runoff through Depressions Implemented using Python and GIS by Zhentao Wang (13042179)

“…<p>A Cell-Based, Dynamic Flow Direction Model (DFD Model) for Water Balance Calculations Simulating Overland Runoff through Depressions Implemented using Python and GIS</p>…”

Parameters and units for the Microbial Consumer Resource Model. by Robert Marsland (8616483)