Probabilistic-QSR-GeoQA by Mohammad Kazemi (19442467)

“…</p><p><br></p><p><br></p><p dir="ltr"><b>Perquisites</b></p><p dir="ltr">Two spatial reasoning tools, SparQ for conventional reasoning and Probcog for probabilistic reasoning need to be installed:</p><p><br></p><p dir="ltr">- Probcog ( Follow the their github repo in https://github.com/opcode81/ProbCog)</p><p dir="ltr">- SparQ (Follow their manual in https://www.uni-bamberg.de/fileadmin/sme/SparQ/SparQ-Manual.pdf)</p><p><br></p><p><br></p><p dir="ltr"><b>Materials</b></p><p dir="ltr">This includes codes, data, evidence sets, and mln folders for two experiments:</p><p dir="ltr">- Code: This folder includes questionGenerator.py and answerExtraction.py for generating synthetic questions and post-processing of inferences from Probcog and SparQ reasoners. …”

A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification by Mohammed Nasser Al-Andoli (21431681)

“…<p dir="ltr">The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts:<br>Python scripts for data preprocessing and integration</p><ul><li>Autoencoder implementation for multimodal feature learning</li><li>Hybrid ensemble training code (DL/ML models and meta-learner)</li><li>PSO and backpropagation hybrid optimization code</li><li>Parallel execution scripts</li><li>Instructions for replicating results on TCGA Pan-cancer and BRCA datasets</li></ul><p></p>…”

<b>Algorithm Pseudocode</b> by Yibin Zhao (22425801)

“…The model generates point forecasts and forecast interval boundaries for short-term loads, providing important support for risk quantification and decision-making in power systems. The pseudo-code follows standard Python syntax specifications for functions and loops and is easy to understand and implement. …”

<b>Anonymous, runnable artifact for </b><b>Testing AI Applications Under Nondeterminism, Drift, and Resource Constraints: A Problem‑Driven Multi‑Layer Approach</b> by Nariman Mani (21380459)

“…</b> The anonymized archive includes a dependency‑free Python implementation of all five layers (oracle, coverage, drift mapping, prioritization, resource scheduling), an orchestrator, and synthetic datasets with 50 test cases per sub‑application (LLM assistant, retrieval with citation, vision calories, notification/social). …”

Curvature-Adaptive Embedding of Geographic Knowledge Graphs in Hyperbolic Space by chenchen Guo (21327470)

“…</p><h3>Requirements</h3><ul><li>Python 3.7</li><li>PyTorch 1.10.0 & CUDA 11.8</li></ul><h3>Main Result Running commands:</h3><p dir="ltr">Execute <code>.sh: bash .…”

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. …”

Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas by Pedro Cabral (18947566)

“…<p dir="ltr">A Python script used for modeling forest GPP in China´s Protected Areas, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), implementation of four machine learning models to predict forest GPP, XAI and causality analysis.…”

MCCN Case Study 3 - Select optimal survey locality by Donald Hobern (21435904)

“…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…”

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. …”

Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2) by Tahir Bhatti (20961974)

“…The pipeline integrates established open-source tools (fastp, BWA-MEM, samtools, iVar, bcftools) and implements <b>codon-aware mutation calling</b> at five canonical RBD positions (R346, S371, K444, F456, F486) relative to NC_045512.2. …”

Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds by Gloria Castañeda-Valencia (20758502)

“…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”

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). …”

Advancing Solar Magnetic Field Modeling by Carlos António (21257432)

“…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …”

kececilayout by Mehmet Keçeci (14301782)

“…<p dir="ltr"><b>Kececi Layout (Keçeci Yerleşimi)</b>: A deterministic graph layout algorithm designed for visualizing linear or sequential structures with a characteristic "zig-zag" or "serpentine" pattern.</p><p dir="ltr"><i>Python implementation of the Keçeci layout algorithm for graph visualization.…”

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++. …”

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. …”

High-throughput chemical genetics screen and titration of hit compounds vinblastine and vincristine. by Emiri Nakamura (21601773)

“…Scale bar = 100μm. (F) Fiji and Python scripts were used to process, analyze, and plot the high-content high-throughput confocal imaging data. …”