Search Results for "framework"
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Showing 23 open source projects for "framework"
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Fuzzy machine learning framework
A library and a GUI front-end for fuzzy machine learning
Fuzzy machine learning framework is a library and a GUI front-end for machine learning using intuitionistic fuzzy data. The approach is based on the intuitionistic fuzzy sets and the possibility theory. Further characteristics are fuzzy features and classes; numeric, enumeration features and features based on linguistic variables; user-defined features; derived and evaluated features; classifiers as features for building hierarchical systems; automatic refinement in case of dependent features; incremental learning; fuzzy control language support; object-oriented software design with extensible objects and automatic garbage collection; generic data base support through ODBC or SQLite; text I/O and HTML output; an advanced graphical user interface based on GTK+; and examples of use. -
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GNSS-SDR
An open source software-defined GNSS receiver
An open source software-defined Global Navigation Satellite Systems (GNSS) receiver written in C++ and based on the GNU Radio framework. -
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Frevo
Frevo is probably the simplest tool for evolutionary design
FREVO is an open-source framework developed in Java to help engineers and scientists in evolutionary design or optimization tasks. The major feature of FREVO is the componentwise decomposition and separation of the key building blocks for each optimization tasks. We identify these as the problem definition, solution representation and the optimization method. This structure enables the components to be designed separately allowing the user to easily swap and evaluate different configurations and methods or to connect an external simulation tool. ... -
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DIG
A library for graph deep learning research
The key difference with current graph deep learning libraries, such as PyTorch Geometric (PyG) and Deep Graph Library (DGL), is that, while PyG and DGL support basic graph deep learning operations, DIG provides a unified testbed for higher level, research-oriented graph deep learning tasks, such as graph generation, self-supervised learning, explainability, 3D graphs, and graph out-of-distribution. If you are working or plan to work on research in graph deep learning, DIG enables you to develop your own methods within our extensible framework, and compare with current baseline methods using common datasets and evaluation metrics without extra efforts. It includes unified implementations of data interfaces, common algorithms, and evaluation metrics for several advanced tasks. Our goal is to enable researchers to easily implement and benchmark algorithms. -
Desktop and Mobile Device Management SoftwareDesktop Central is a unified endpoint management (UEM) solution that helps in managing servers, laptops, desktops, smartphones, and tablets from a central location.
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AllenNLP
An open-source NLP research library, built on PyTorch
AllenNLP makes it easy to design and evaluate new deep learning models for nearly any NLP problem, along with the infrastructure to easily run them in the cloud or on your laptop. AllenNLP includes reference implementations of high quality models for both core NLP problems (e.g. semantic role labeling) and NLP applications (e.g. textual entailment). AllenNLP supports loading "plugins" dynamically. A plugin is just a Python package that provides custom registered classes or additional... -
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Catalyst
Accelerated deep learning R&D
Catalyst is a PyTorch framework for accelerated Deep Learning research and development. It allows you to write compact but full-featured Deep Learning pipelines with just a few lines of code. With Catalyst you get a full set of features including a training loop with metrics, model checkpointing and more, all without the boilerplate. Catalyst is focused on reproducibility, rapid experimentation, and codebase reuse so you can break the cycle of writing another regular train loop and make something totally new. ... -
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Dopamine
Framework for prototyping of reinforcement learning algorithms
Dopamine is a research framework for fast prototyping of reinforcement learning algorithms. It aims to fill the need for a small, easily grokked codebase in which users can freely experiment with wild ideas (speculative research). This first version focuses on supporting the state-of-the-art, single-GPU Rainbow agent (Hessel et al., 2018) applied to Atari 2600 game-playing (Bellemare et al., 2013). -
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DaNNet
Deep Artificial Neural Network framework using Armadillo
DaNNet is a C++ deep neural network library using the Armadillo library as a base. It is intended to be a small and easy to use framework with no other dependencies than Armadillo. It uses independent layer-wise optimization giving you full flexibility to train your network. -
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Acoustic Research Tool (ART)
Acoustic Simulation Library for Frequency and Time Domain Simulations.
ART is a flexible simulation framework for wind instruments. It includes a growing library of modelling elements. So far bore discontinuities, branches, tone holes, cylindrical and conical tubes, Bessel horns and bent tubes are available for frequency domain modelling. In the time domain generic bidirectional propagation elements, scattering elements, fractional delays, convolution with reflection functions and general z-domain networks are available and can be described using MuParserX expressions. ... -
Lenso.ai is a perfect example of an AI image search toolLenso.ai is a perfect example of an AI image search tool, where you can simply search for images that you are most interested in. Thanks to advanced AI technology implemented on lenso.ai, you can easily start searching for places, people, duplicates, related or similar images.
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Bibliograph
Open Source Online Bibliographic Data Management
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. -
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StochKit is an extensible stochastic simulation framework developed in C++ that aims to make stochastic simulation accessible to practicing biologists and chemists, while remaining open to extension via new stochastic and multiscale algorithms. StochKit is part of the StochSS project [http://www.stochss.org/], and we are relying on continued funding for sustained development. Please consider registering to show your support.
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MoRe4ABM
Managing Ongoing RElationships for Agent-Based Modelling
The purpose of MoRe4ABM - Managing Ongoing RElationships for ABM - is to support representing and analysing social networks in agent-based modeling. The library provides a large number of network generators and a comprehensive framework for network and node level measures. It integrates well with Repast Simphony and uses the JUNG library. More4ABM furthermore supports initialisation of geographically explicit networks using GIS. -
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S-Match
S-Match is a semantic matching framework.
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. -
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ReBAC Java Library
ReBAC library for java development
Java library for Relationship Based Access Control (ReBAC). Provides a general framework creating ReBAC policies and model checking. Also provides tools for testing. Obtain latest version as a Maven Dependency: <dependency> <groupId>ca.ucalgary.ispia</groupId> <artifactId>rebac</artifactId> <version>0.1.7</version> </dependency> -
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GraphEA
A 3D Graphical Framework for Exploring Evolutionary Algorithms
Perfect to explore in the classroom: * Choose different problems, for different representations * Choose different genetic operators * Configure parameters * Visualization of the results on-line * Stop, pause or resume the evolutionary process * Explore how the genetic operators work * Save the results for future analysis -
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dwos
dwos is a distribute WEB-desktop OS and scientific computing platform
...It mainly contains a WEB desktop environment, a chat-online system, a network disk system, a Scientific Computing platform(developing) and so on. It is developed by JAVA language using the JSH(JSF+Spring+Hibernate) framework. After about half year testing, now it's open source, you can download it and run on your computer, Tomcat and jetty server container are tested ok. It's developed by myself, more about me, see here: http://home.ustc.edu.cn/~chh1990/chero/chero.html -
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IPSA - Inventor Physics Simulation API
Easy to use physics simulation combining ODE with OpenInventor.
Create phyiscal simulations easily through IPSA which combines the OpenInventor 3D API with the Open Dynamics Engine (ODE). Scenes are read from .iv files and simulated in the supplied viewer applications. Find it at: http://ipsa.sourceforge.net -
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MSR Tools is a source code evolution analysis tool. It consists of a framework for mining software repositories and tools for metric calculation, visualization, defect prediction.
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MarcXimiL is a flexible multi-platform bibliographic similarity analysis framework. Features: deduplication, information monitoring, visual analysis, plagiarism detection. Supported: MARCXML, OAI-PMH2 harvesting, and importation of text MARC.
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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.
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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.
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This project aims to build a portable pure C++ framework for GPGPU operations. It is conceived to ease scientific researches that need to speed up algebric and calculus operations on normal hardware, without the need of graphic programming knowledge.
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