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. …”

Spotted owl habitat quality maps and disturbance attribution analysis by Josh Barry (7573823)

“…<p dir="ltr">This dataset includes annual spatial maps of spotted owl nesting habitat quality in Southern California and an accompanying ArcPython script used to attribute negative annual habitat change to wildfire (Barry et al., 2025). …”

Data and software for "Social networks affect redistribution decisions and polarization" by Milena Tsvetkova (11217969)

“…</p><p dir="ltr">The repository contains data in .csv and .xlsx format, model code in .nlogox Netlogo format, analysis code in .ipynb Jupyter notebooks, and helping code in .py Python files.…”

RabbitSketch by tong zhang (20852432)

“…RabbitSketch achieves significant speedups compared to existing implementations, ranging from 2.30x to 49.55x.In addition, we provide flexible and easy-to-use interfaces for both Python and C++. …”

face recognation with Flask by Muammar, SST, M.Kom (21435692)

“…Built using the <b>Flask</b> web framework (Python), this system provides a lightweight and scalable solution for implementing facial recognition capabilities in real-time or on-demand through a browser interface.…”

Keyhole Imagery Global Coverage Dataset (1960–1984) by Hao Li (20223762)

“…</li><li><b>Code</b>: Python scripts implementing the three-step workflow (imagery classification, global grid generation, and point-based property calculation).…”

Recursive generation of substructures using point data by Jackie R (18359715)

“…<p dir="ltr">The dataset contains generated substructure using POI in China, the pseudo code for the algorithm and python implement of the algorithm. …”

Demonstration of Isosteric Heat of Adsorption Calculation using AIFs and pyGAPs by Jack Evans (11275386)

“…</p><p dir="ltr">The calculation is performed using the Clausius-Clapeyron method as implemented in the <code><strong>pyGAPS</strong></code> Python library for adsorption science. …”

<b>Testing AI Applications Under Nondeterminism, Drift, and Resource Constraints</b> by Nariman Mani (21380459)

“…<ul><li>A <b>Python repo</b> with minimal implementations of all five layers<br>(<b>COL</b>, <b>SCL</b>, <b>CDM</b>, <b>RPE</b>, <b>RAS</b>) plus an <b>orchestrator</b> and utilities.…”

Soulware-Lite by Abhiram Gnyanijaya (21572942)

“…It operates as middleware to intercept user inputs and LLM outputs, performing real-time semantic auditing, belief-state tracking, introspective alignment scoring (KRW, deltaΨ), and automated self-correction.…”

Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) by Amanda Bueno de Moraes (22559249)

“…The code implements a statistical–computational workflow for parameter selection (VIF, Bartlett and KMO tests, PCA and FA with <i>varimax</i>) and then trains and evaluates machine-learning models to predict three key physico-chemical indicators: turbidity, true color, and total iron. …”

Table & Figure.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

“…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”

Raw Data EEG.pdfBrainwaves and Higher-Order Thinking: An EEG Study of Cognitive Engagement in Mathematics Tasks by NORLIZA BINTI MOHAMED (20739875)

“…Supplementary Materials</p> <p><br></p> <p>Experimental protocols and study design details</p> <p><br></p> <p>Questionnaires, surveys, or rubrics used in the study</p> <p><br></p> <p>Educational materials related to HOTS-based mathematics tasks</p> <p><br></p> <p><br></p> <p><br></p> <p>3. Code and Algorithms (if applicable)</p> <p><br></p> <p>Scripts for EEG signal processing and analysis</p> <p><br></p> <p>Machine learning or statistical modeling scripts</p> <p><br></p> <p>Any software implementation used to analyze brainwave patterns</p> <p><br></p> <p><br></p> <p><br></p> <p>4. …”

Online Resource: Reservoir Computing as a Promising Approach for False Data Injection Attack Detection in Smart Grids by Carl-Hendrik Peters (21530624)

“…</li><li><b>3_literature_analysis_and_mapping.ipynb</b><br>Contains the Python code used for executing the systematic mapping study (SMS), including automated processing of literature data and thematic clustering.…”

PYSEQM 2.0: Accelerated Semiempirical Excited-State Calculations on Graphical Processing Units by Vishikh Athavale (12623809)

“…We report the development and implementation of electronic excited-state capabilities for semiempirical quantum chemical methods at both the Configuration Interaction Singles and Time-Dependent Hartree–Fock levels of theory, integrated within the PYSEQM 2.0 software package (https://github.com/lanl/PYSEQM). …”

Probabilistic-QSR-GeoQA by Mohammad Kazemi (19442467)

“…<p dir="ltr">The code and data are related to the paper Mohammad Kazemi Beydokhti, Matt Duckham, Amy L. …”

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)

“…This repository provides the raw data, the complete imputed daily dataset, imputation statistics, a data dictionary, the Python code used (Imputation_Air_Pollutants_NABEL.py), smoothed time-series plots (28-day running average), and a comparative table of winter pollutant burdens 2016–2019. …”

A Fully Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture by Nagarajan Kandasamy (8400168)

“…QUANTISENC’s software-defined hardware design methodology allows the user to train an SNN model using Python and evaluate performance of its hardware implementation, such as area, power, latency, and throughput. …”

Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx by Piyachat Udomwong (22563212)

“…Its efficiency and scalability make it well-suited for early-stage antibody discovery, repertoire profiling, and therapeutic design, particularly in the absence of structural data. The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”

Concurrent spin squeezing and field tracking with machine learning by Junlei Duan (18393642)

“…<p dir="ltr">The dataset contains:</p><ol><li>Steady_squeezing.zip <b>a)</b> data for steady squeezing data and characteraztion <b>b)</b> data for pulse RF magnetormeter</li><li>Tracking1.zip <b>a)</b> data of OU process for Deep learning <b>b)</b> data of OU-jump process for Deep learning</li><li>Tracking2.zip <b>a)</b> data of white noise process in backaction experiment <b>b) </b>data of white noise process in rearrange experiment</li><li>Code <b>a)</b> Randomly signal generating code <b>b)</b> Deep learning codec.data pre-processing code</li></ol><p dir="ltr">The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …”