Search Results for "data capture framework"

...Built with simplicity and extensibility in mind, the project includes REST APIs, database models, and a user interface that can be extended or embedded into existing internal systems. Because it prioritizes lean data structures and predictable code paths, developers can customize pipelines, fields, and behaviors to align with their unique business logic.

Megatron-LM is a GPU-optimized deep learning framework from NVIDIA designed to train extremely large transformer-based language models efficiently at scale. The repository provides both a reference training implementation and Megatron Core, a composable library of high-performance building blocks for custom large-model pipelines. It supports advanced parallelism strategies including tensor, pipeline, data, expert, and context parallelism, enabling training across massive multi-GPU and multi-node clusters. ...

Bibliograph is a powerful and intuitive open source web application for the collaborative collection, editing and publishing of bibliographic data such as a bibliographies, small library collections or shared research data. It features a modern user interface similar to a desktop application.

S-Match is a semantic matching framework. S-Match takes any two tree like structures (such as database schemas, classifications, lightweight ontologies) and returns a set of correspondences between those tree nodes which semantically correspond to one another. S-Match contains implementations of the semantic matching, minimal semantic matching and structure preserving semantic matching algorithms. S-Match applies as a solution in many fields, including: information integration,...

Biomedical Information Management System (BIMS) is a modular multilayer object - oriented software architecture, which provides a flexible computational solution to capture and manage a heterogeneous biomedical data: textual and visual information.

This research project seeks to use compiler techniques to perform an attribute-based data-flow analysis on (MOF/UML)models allowing for a syntax-driven validation of a model's static semantics as well as an abstract interpretation of i dynamic behavior.

Facilitates data mining/natural language processing experiments to be executed on weblogs, such as classification, clustering and rating. As part of these experiments, it is possible to apply Latent Semantic Analysis.