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practical implementation » practical implications (Expand Search)
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python model » python code (Expand Search), python tool (Expand Search), action model (Expand Search)
practical implementation » practical implications (Expand Search)
model implementation » modular implementation (Expand Search), world implementation (Expand Search), time implementation (Expand Search)
python model » python code (Expand Search), python tool (Expand Search), action model (Expand Search)
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Python Code for Fine-Tuned BERT Model in High School Student Advising
Published 2025“…<p dir="ltr">This repository contains the Python implementation and fine-tuned BERT model for answering high school student questions on college and career advising, based on the methodology described in Assayed et al. (2024). …”
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ALAAM models for the Deezer networks, with liking “alternative” music as the outcome variable.
Published 2024Subjects: -
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Models estimated using ALAAMEE for the Deezer networks, with liking jazz as the outcome variable.
Published 2024Subjects: -
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Survey Dataset and Python Code for Preprocessing, Statistical Tests
Published 2025“…Supporting figures and tables are available in the repository</p><p dir="ltr">Data processing was implemented in Python 3.11 and attached are all the python scripts used for preprocessing , and statistical Analysis and also the questionnaire used for the study.…”
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Python code for a rule-based NLP model for mapping circular economy indicators to SDGs
Published 2025“…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…”
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Supporting data for "Interpreting complex ecological patterns and processes across differentscales using Artificial Intelligence"
Published 2025“…</p><p dir="ltr">Secondly, at the population level, deep learning (DL) models were benchmarked to inform the best practices in quantifying distribution patterns of intertidal mussels over large spatial scales. …”
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Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout.
Published 2025“…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …”
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ZILLNB_Model
Published 2025“…<p dir="ltr">Acquire latent variables using deep-learning based model implemented in python</p>…”
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Cost functions implemented in Neuroptimus.
Published 2024“…To address these issues, we developed a generic platform (called Neuroptimus) that allows users to set up neural parameter optimization tasks via a graphical interface, and to solve these tasks using a wide selection of state-of-the-art parameter search methods implemented by five different Python packages. Neuroptimus also offers several features to support more advanced usage, including the ability to run most algorithms in parallel, which allows it to take advantage of high-performance computing architectures. …”
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BSTPP: a python package for Bayesian spatiotemporal point processes
Published 2025“…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. …”
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Type II error rate from estimation of simulated outcomes using the EE algorithm.
Published 2024Subjects: -
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