torch-geometric
π―Skillfrom swn94/claude-scientific-skills
Simplifies graph neural network development with PyTorch Geometric, enabling efficient node, edge, and graph-level machine learning tasks.
Part of
swn94/claude-scientific-skills(145 items)
Installation
npx skills add https://github.com/swn94/claude-scientific-skills --skill torch-geometricNeed more details? View full documentation on GitHub β
More from this repository10
Performs advanced statistical analysis with regression, hypothesis testing, data visualization, and machine learning model evaluation across various datasets
Converts scientific documents and research notes into clean, structured Markdown with proper formatting, citations, and LaTeX equation support.
Efficiently manage and manipulate large, chunked, compressed N-dimensional arrays in scientific computing and data analysis workflows using Zarr.
Streamlines scientific image data management by connecting Python workflows with OMERO's remote microscopy repository and metadata systems
Simplifies scientific computing by providing powerful symbolic mathematics, numerical integration, and plotting capabilities for Python research and engineering tasks.
Performs astronomical data analysis, coordinate transformations, and astrophysical calculations using Python's premier scientific astronomy library.
Queries and retrieves chemical, biological, and pharmacological data from the ChEMBL database for drug discovery and research insights.
Queries and analyzes biological pathway data from the Reactome database, enabling researchers to explore gene interactions and molecular mechanisms.
Retrieves and processes genomic data from the Ensembl database, enabling quick gene, transcript, and variant information extraction for bioinformatics research.
Retrieves, filters, and analyzes clinical trial data from ClinicalTrials.gov using advanced search and metadata extraction techniques