BSTPP: a python package for Bayesian spatiotemporal point processes by Isaac Manring (20705955)

“…However, they are sometimes neglected due to the difficulty of implementing them. There is a lack of packages with the ability to perform inference for these models, particularly in python. …”

Python Implementation of HSGAdviser Chatbot: AI model for Sustainable Education by Suha Assayed (22454038)

“…<p dir="ltr">This repository contains the Python source code and model implementation for HSGAdviser, an AI speech assistant designed to provide personalized college and career guidance for high school students through conversational AI. …”

Python scripts and notebooks by Ismail Belgacem (20845811)

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

“…A license key is generated, allowing authorized users to access the code.bash<pre><pre>python secure_python_code_manager.py --upload -f your_script.py<br></pre></pre></li><li><b>Updating Previously Uploaded Code</b>: With the <code>--update</code> function, update your code in the cloud without needing to redistribute new files to clients, ensuring seamless code maintenance and updates.bash<pre><pre>python secure_python_code_manager.py --update -f your_script.py -l your_license_key<br></pre></pre></li><li><b>Retrieving License Information</b>: The <code>--license-info</code> function lets you retrieve detailed information about your licenses, including status, usage data, and limits.bash<pre><pre>python secure_python_code_manager.py --license-info -l your_license_key<br></pre></pre></li><li><b>Service Usage Monitoring</b>: Use the <code>--service-usage</code> function to monitor your service usage, including uploaded scripts and associated licenses, helping you keep track of your code deployment.bash<pre><pre>python secure_python_code_manager.py --service-usage<br></pre></pre></li></ol><h2>Use Cases</h2><ul><li><b>Protect Python Code</b>: If you're looking to <b>protect Python code</b> from unauthorized use, this tool provides robust protection mechanisms.…”

Python script multiclass RoBERTa by Maija Ozola-Schade (20938460)

Python script for binary classification with RoBERTa by Maija Ozola-Schade (20938460)

Online Resource 3: Word Cloud Dataset and Code by Jessica Zylla (17692920)

“…This set of files are part of Online Resource 3, which allows readers to implement a Jupyter Notebook Python program to create a word cloud based on survey responses. …”

This package of Python scripts implements the proposed unsupervised sentiment analysis approach.... by Xiaohan Yu (7525940)

“…<p>This package of Python scripts implements the proposed unsupervised sentiment analysis approach. …”

Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789 by Jordan Waters (21620558)

“…<br><br><br><b>ORCID ID: https://orcid.org/0009-0009-0793-8089</b><br></p><p dir="ltr"><b>Code Availability:</b></p><p dir="ltr"><b>All Python tools used for GoP simulations and predictions are available at:</b></p><p dir="ltr"><b>https://github.com/Jwaters290/GoP-Probabilistic-Curvature</b><br><br>The Gravity of Probability framework is implemented in this public Python codebase that reproduces all published GoP predictions from preexisting DESI data, using a single fixed set of global parameters. …”

Explained variance ration of the PCA algorithm. by Abeer Aljohani (18497914)

“…All our simulation is performed in computation softwares, Matlab and Python. The image pre processing and spectral moments generation is performed in Matlab and the implementation of the classifiers is performed with python. …”

Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" by Krishnendu Chatterjee (15367413)

“…</p><h2>Dependencies</h2><p dir="ltr">In order to run the code the following dependencies must be met:</p><pre><pre>- Python 3 should be installed. We used Python 3.9 to obtain the results in the paper. …”

The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network" by Chongshan Wan (19247614)

“…</li></ul><h2>Running the Code</h2><h3><b>Data processing and feature extraction</b></h3><pre>python run_process.py</pre><p dir="ltr">This step processes trajectory data, extracts graph node features and edge features, and saves them as CSV files in the `processed_data` folder.…”

adnus by Mehmet Keçeci (14301782)

“…<p dir="ltr">adnus (AdNuS): Advanced Number Systems</p><p dir="ltr">adnus is a Python library that provides an implementation of various advanced number systems. …”

Missing Value Imputation in Relational Data Using Variational Inference by Simon Fontaine (7046618)

“…Additional results, implementation details, a Python implementation, and the code reproducing the results are available online. …”

<b>Data Availability</b> by Bonyad Ahmadi (20750327)

“…</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.…”

<b>Data Availability</b> by Bonyad Ahmadi (20750327)

“…</p><p dir="ltr">python scripts documenting the implementation of the Mixture Density Network (MDN) algorithm, including hyperparameter tuning and uncertainty quantification.…”

Ambient Air Pollutant Dynamics (2010–2025) and the Exceptional Winter 2016–17 Pollution Episode: Implications for a Uranium/Arsenic Exposure Event by Thomas Clemens Carmine (19756929)

“…<br><br><b>Missing-Data Handling & Imputation:</b></p><p dir="ltr">The following sequential steps were applied to create a complete and consistent daily time series suitable for analysis (presented in the Imputed_AP_Data_Zurich_2010-25 sheet), particularly addressing the absence of routine PM₂.₅ measurements prior to January 2016. The full implementation is detailed in the accompanying Python script (Imputation_Air_Pollutants_NABEL.py). …”

Parallel Sampling of Decomposable Graphs Using Markov Chains on Junction Trees by Mohamad Elmasri (19421498)

“…We find that our parallel sampler yields improved mixing properties in comparison to the single-move variate, and outperforms current state-of-the-art methods in terms of accuracy and computational efficiency. The implementation of our work is available in the Python package parallelDG. …”

Gene Editing using Transformer Architecture by Rishabh Garg (5261744)

“…</p><p dir="ltr">Once TASAG detects a deviation from a reference sequence (e.g., the H-Bot sequence), it facilitates on-screen gene editing, enabling targeted mutations or the insertion of desired genes. Implementation requires Python and deep learning frameworks like TensorFlow or PyTorch, with optional use of Biopython for genetic sequence handling. …”

Bayesian Changepoint Detection via Logistic Regression and the Topological Analysis of Image Series by Andrew M. Thomas (712104)

“…The method also successfully recovers the location and nature of changes in more traditional changepoint tasks. An implementation of our method is available in the Python package bclr.…”