Search Results for "ai research"
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Showing 25 open source projects for "ai research"
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Bacalhau
Community-driven, simple, yet powerful framework
...Bacalhau supports various runtime environments and is designed to make decentralized data processing as accessible as traditional cloud computing. It’s especially useful for large-scale AI/ML jobs, scientific research, and content indexing in Web3 ecosystems. -
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Flower
Flower: A Friendly Federated Learning Framework
...Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new state-of-the-art systems. Different machine learning frameworks have different strengths. Flower can be used with any machine learning framework, for example, PyTorch, TensorFlow, Hugging Face Transformers, PyTorch Lightning, scikit-learn, JAX, TFLite, MONAI, fastai, MLX, XGBoost, Pandas for federated analytics, or even raw NumPy for users who enjoy computing gradients by hand. -
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Fabric
Fabric is an open-source framework for augmenting humans using AI
Fabric is a command-line framework that turns a curated library of prompt “patterns” into reusable, automatable workflows for large language models. Instead of repeatedly crafting ad-hoc prompts, you pick a pattern (for research, summarization, brainstorming, code review, and more) and feed it inputs or files. The tool standardizes execution with configuration files and environment variables, enabling reproducible runs across different models and providers. Patterns can be customized with... -
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TorchGAN
Research Framework for easy and efficient training of GANs
The torchgan package consists of various generative adversarial networks and utilities that have been found useful in training them. This package provides an easy-to-use API which can be used to train popular GANs as well as develop newer variants. The core idea behind this project is to facilitate easy and rapid generative adversarial model research. TorchGAN is a Pytorch-based framework for designing and developing Generative Adversarial Networks. This framework has been designed to... -
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HyperGAN
Composable GAN framework with api and user interface
A composable GAN built for developers, researchers, and artists. HyperGAN builds generative adversarial networks in PyTorch and makes them easy to train and share. HyperGAN is currently in pre-release and open beta. Everyone will have different goals when using hypergan. HyperGAN is currently beta. We are still searching for a default cross-data-set configuration. Each of the examples supports search. Automated search can help find good configurations. If you are unsure, you can start with... -
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MMF
A modular framework for vision & language multimodal research
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-the-art vision and language models and has powered multiple research projects at Facebook AI Research. MMF is designed from ground up to let you focus on what matters, your model, by providing boilerplate code for distributed training, common datasets and state-of-the-art pre-trained baselines out-of-the-box. ... -
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BWAPI
An API for interacting with Starcraft: Brood War (1.16.1)
Brood War Application Programming Interface or BWAPI is a free and open source C++ framework that is used to create Artificial Intelligence (AI) agents that play the popular Real Time Strategy (RTS) game Starcraft: Brood War. With BWAPI, players of varying levels can create AI agents to play Brood War, but with certain limits. BWAPI will only reveal visible parts of the game state to AI modules to enable programmers to write competitive non-cheating AIs. BWAPI also denies user input so... -
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Caffe Framework
Caffe, a fast open framework for deep learning
Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his PhD at UC Berkeley. Caffe is released under the BSD 2-Clause license. Expressive architecture encourages application and innovation. Models and optimization are defined by configuration without hard-coding. Switch between CPU and GPU by setting a single flag to train on a GPU machine then deploy to commodity clusters or mobile devices. ... -
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Caffe
A fast open framework for deep learning
...Caffe also offers great speed, capable of processing over 60M images per day with a single NVIDIA K40 GPU. It’s arguably one of the fastest convnet implementations around. Caffe is developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and a great community of contributors that continue to make Caffe state-of-the-art in both code and models. It’s been used in numerous projects, from startup prototypes and academic research projects, to large scale industrial applications. -
Total Network Visibility for Network Engineers and IT ManagersThis means every device on your network, and every interface on every device is automatically analyzed for performance, errors, QoS, and configuration.
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JCLTP
A Java Class Library for Text Processing
JCLTP is a class library designed for processing text. JCLTP is free, open source and developed with the Java programming language. JCLTP is distributed under the GNU license. It incorporates several technologies that enable process information while applying AI techniques, in order to build predictive models for text classification. Through a flexible structure of interfaces and classes, the opportunity to extend, adapt and add functionality JCLTP is provided. Thus, analysis of new types... -
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ajile
Advanced JavaScript Importing & Loading Extension
ajile: Advanced JavaScript Importing & Loading Extension allows developers to easily create unique namespaces for JavaScript modules and quickly define dependencies that allow scripts to automatically load and import each other as needed. -
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A software toolkit that implements the CoSy Architecture Schema for developing integrated intelligent robotic systems. The toolkit focuses on supporting on a space of information-processing architectures based on shared working memories.
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Library for creation of artificial neural networks in C#. Library supports Hopfield nets, Kohonen nets, feedforward networks, several learning techniques (differential evolution, back propagation, quick propagation, resilient propagation etc.)
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Web-as-corpus tools in Java. * Simple Crawler (and also integration with Nutch and Heritrix) * HTML cleaner to remove boiler plate code * Language recognition * Corpus builder
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PlexBench is a cross-platform, web-enabled, analysis tool that is driven by a scalable backpropagation feed-forward neural network. It uses embedded Perl for scripting and is written in the style of an in-process Component Object Model (COM) C++ program.
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NeuronDotNet is a neural network engine written in C#. It provides an interface for advanced AI programmers to design various types of artificial neural networks and use them.
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jSemanticService is a lightweight framework that allows to use Rules and Semantics in Services or Applications using Annotations. Features: jBoss Rules (Drools 4.0) as Business Rules Engine provider. Full support of Annotations, Spring, Flex/Blaze DS.
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Using this plugin-based framework, you can instantly start working on the *brain* of your bot (irc bot, chatterbot, robot, ...). With support for db, irc, logging and programming-language independent plugins, users can easily enhance the functionality.
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CAIR is an e-learning project that allow users and subjects management. You can associate pupils and teachers to subjects and works for this subjects. There are special functionalities for those subjects related to Robocup development.
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MAIF is developed in Java 5 (especially Generics) and aims at building AI algorithms, by concentrating onto the mapping of real-world problems, while abstracting from their inner working. It can be extended with new algorithms and problem representations.
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This is a framework to develop Contexts and Agents and a Container to run them. The Container lets each Agent interact with the Context and other Agents. The agents are deployed in jar files and each one runs in an exclusive sandbox.
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GameBots# is a client API written in C# for GameBots, a research-oriented platform for building artificially-intelligent autonomous agents for computer games.
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Robot Controlling System (RCS) - is a .NET-oriented software group for controlling remote mechanical objects, debuging and programming them by .NET-languages
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Plansim is a C++ framework aimed to the development of efficient planner agents based on heuristic forward search, that use discrete event simulators as the model for the agent's environment.
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