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code implementation » model implementation (Expand Search), time implementation (Expand Search), world implementation (Expand Search)
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101
BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories
Published 2025“…We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”
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102
Data Sheet 1_COCαDA - a fast and scalable algorithm for interatomic contact detection in proteins using Cα distance matrices.pdf
Published 2025“…Here, we introduce COCαDA (COntact search pruning by Cα Distance Analysis), a Python-based command-line tool for improving search pruning in large-scale interatomic protein contact analysis using alpha-carbon (Cα) distance matrices. …”
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103
HCC Evaluation Dataset and Results
Published 2024“…The only requirement for running this script is a Python 3.6+ interpreter as well as an installation of the <code>numpy</code> package. …”
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104
Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis
Published 2025“…</p><h2><b>Included Files</b></h2><h3><b>1. </b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.…”
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105
The artifacts and data for the paper "DD4AV: Detecting Atomicity Violations in Interrupt-Driven Programs with Guided Concolic Execution and Filtering" (OOPSLA 2025)
Published 2025“…</p><pre><pre>sudo apt-get install -y wget git build-essential python3 python python-pip python3-pip tmux cmake libtool libtool-bin automake autoconf autotools-dev m4 autopoint libboost-dev help2man gnulib bison flex texinfo zlib1g-dev libexpat1-dev libfreetype6 libfreetype6-dev libbz2-dev liblzo2-dev libtinfo-dev libssl-dev pkg-config libswscale-dev libarchive-dev liblzma-dev liblz4-dev doxygen libncurses5 vim intltool gcc-multilib sudo --fix-missing<br></pre></pre><pre><pre>pip install numpy && pip3 install numpy && pip3 install sysv_ipc<br></pre></pre><h4><b>Download the Code</b></h4><p dir="ltr">Download <b>DD4AV</b> from the Figshare website to your local machine and navigate to the project directory:</p><pre><pre>cd DD4AV<br></pre></pre><h4><b>Configure Environment and Install the Tool</b></h4><p dir="ltr">For convenience, we provide shell scripts to automate the installation process. …”
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106
Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games"
Published 2024“…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…”
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107
<b>Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population</b>
Published 2025“…<p dir="ltr">Contains</p><p dir="ltr">Final Analysis Output.xlsx: Current and reference concentrations of DRP, TP, NO3-N and TN along with pivot table analysis</p><p dir="ltr">Code: Python code used to implement the model in ArcGIS Pro.…”
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108
Probabilistic-QSR-GeoQA
Published 2024“…</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. …”
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109
A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification
Published 2025“…<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>…”
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110
<b>Algorithm Pseudocode</b>
Published 2025“…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. …”
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111
<b>Anonymous, runnable artifact for </b><b>Testing AI Applications Under Nondeterminism, Drift, and Resource Constraints: A Problem‑Driven Multi‑Layer Approach</b>
Published 2025“…</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). …”
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112
Curvature-Adaptive Embedding of Geographic Knowledge Graphs in Hyperbolic Space
Published 2025“…</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 .…”
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113
Void-Center Galaxies and the Gravity of Probability Framework: Pre-DESI Consistency with VGS 12 and NGC 6789
Published 2025“…<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. …”
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114
MCCN Case Study 3 - Select optimal survey locality
Published 2025“…</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>…”
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115
Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas
Published 2025“…<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.…”
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116
Genomic Surveillance of Pemivibart (VYD2311) Escape-Associated Mutations in SARS-CoV-2: December 2025 BioSamples (n=2)
Published 2025“…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. …”
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117
Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds
Published 2025“…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …”
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118
adnus
Published 2025“…<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. …”
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119
Missing Value Imputation in Relational Data Using Variational Inference
Published 2025“…Additional results, implementation details, a Python implementation, and the code reproducing the results are available online. …”
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120
Spotted owl habitat quality maps and disturbance attribution analysis
Published 2025“…<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). …”