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practical implementation » practical implications (Expand Search)
python model » python code (Expand Search), action model (Expand Search), motion model (Expand Search)
practical implementation » practical implications (Expand Search)
python model » python code (Expand Search), action model (Expand Search), motion model (Expand Search)
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Jaxkineticmodel allows for hybridizing kinetic models with neural networks.
Published 2025Subjects: -
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Cost functions implemented in Neuroptimus.
Published 2024“…In recent years, manual model tuning has been gradually replaced by automated parameter search using a variety of different tools and methods. …”
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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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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. …”